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  • Open Access


    Traffic Sign Detection with Low Complexity for Intelligent Vehicles Based on Hybrid Features

    Sara Khalid1, Jamal Hussain Shah1,*, Muhammad Sharif1, Muhammad Rafiq2, Gyu Sang Choi3,*

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 861-879, 2023, DOI:10.32604/cmc.2023.035595

    Abstract Globally traffic signs are used by all countries for healthier traffic flow and to protect drivers and pedestrians. Consequently, traffic signs have been of great importance for every civilized country, which makes researchers give more focus on the automatic detection of traffic signs. Detecting these traffic signs is challenging due to being in the dark, far away, partially occluded, and affected by the lighting or the presence of similar objects. An innovative traffic sign detection method for red and blue signs in color images is proposed to resolve these issues. This technique aimed to devise an efficient, robust and accurate… More >

  • Open Access


    Robust Image Watermarking Using LWT and Stochastic Gradient Firefly Algorithm

    Sachin Sharma1,*, Meena Malik2, Chander Prabha3, Amal Al-Rasheed4, Mona Alduailij4, Sultan Almakdi5

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 393-407, 2023, DOI:10.32604/cmc.2023.033536

    Abstract Watermarking of digital images is required in diversified applications ranging from medical imaging to commercial images used over the web. Usually, the copyright information is embossed over the image in the form of a logo at the corner or diagonal text in the background. However, this form of visible watermarking is not suitable for a large class of applications. In all such cases, a hidden watermark is embedded inside the original image as proof of ownership. A large number of techniques and algorithms are proposed by researchers for invisible watermarking. In this paper, we focus on issues that are critical… More >

  • Open Access


    A New Three-Parameter Inverse Weibull Distribution with Medical and Engineering Applications

    Refah Alotaibi1, Hassan Okasha2,3, Hoda Rezk4, Mazen Nassar2,5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1255-1274, 2023, DOI:10.32604/cmes.2022.022623

    Abstract The objective of this article is to provide a novel extension of the conventional inverse Weibull distribution that adds an extra shape parameter to increase its flexibility. This addition is beneficial in a variety of fields, including reliability, economics, engineering, biomedical science, biological research, environmental studies, and finance. For modeling real data, several expanded classes of distributions have been established. The modified alpha power transformed approach is used to implement the new model. The data matches the new inverse Weibull distribution better than the inverse Weibull distribution and several other competing models. It appears to be a distribution designed to… More >

  • Open Access


    ILipo-PseAAC: Identification of Lipoylation Sites Using Statistical Moments and General PseAAC

    Talha Imtiaz Baig1,*, Yaser Daanial Khan1, Talha Mahboob Alam2, Bharat Biswal3, Hanan Aljuaid4, Durdana Qaiser Gillani5

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 215-230, 2022, DOI:10.32604/cmc.2022.021849

    Abstract Lysine Lipoylation is a protective and conserved Post Translational Modification (PTM) in proteomics research like prokaryotes and eukaryotes. It is connected with many biological processes and closely linked with many metabolic diseases. To develop a perfect and accurate classification model for identifying lipoylation sites at the protein level, the computational methods and several other factors play a key role in this purpose. Usually, most of the techniques and different traditional experimental models have a very high cost. They are time-consuming; so, it is required to construct a predictor model to extract lysine lipoylation sites. This study proposes a model that… More >

  • Open Access


    On Relations for Moments of Generalized Order Statistics for Lindley–Weibull Distribution

    Faten A. Momen khan1, Saman Hanif Shahbaz2, Muhammad Qaiser Shahbaz2,*

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 197-208, 2022, DOI:10.32604/csse.2022.020448

    Abstract Moments of generalized order statistics appear in several areas of science and engineering. These moments are useful in studying properties of the random variables which are arranged in increasing order of importance, for example, time to failure of a computer system. The computation of these moments is sometimes very tedious and hence some algorithms are required. One algorithm is to use a recursive method of computation of these moments and is very useful as it provides the basis to compute higher moments of generalized order statistics from the corresponding lower-order moments. Generalized order statistics provides several models of ordered data… More >

  • Open Access


    iPhosD-PseAAC: Identification of phosphoaspartate sites in proteins using statistical moments and PseAAC


    BIOCELL, Vol.45, No.5, pp. 1287-1298, 2021, DOI:10.32604/biocell.2021.013770

    Abstract Phosphoaspartate is one of the major components of eukaryotes and prokaryotic two-component signaling pathways, and it communicates the signal from the sensor of histidine kinase, through the response regulator, to the DNA alongside transcription features and initiates the transcription of correct response genes. Thus, the prediction of phosphoaspartate sites is critical, and its experimental identification can be expensive, time-consuming, and tedious. For this purpose, we propose iPhosD-PseAAC, a new computational model for predicting phosphoaspartate sites in a particular protein sequence using Chou’s 5-steps rues: (1) Benchmark dataset. (2) The feature extraction techniques such as pseudo amino acid composition (PseAAC), statistical… More >

  • Open Access


    Parameter Estimation of Alpha Power Inverted Topp-Leone Distribution with Applications

    Gamal M. Ibrahim1, Amal S. Hassan2, Ehab M. Almetwally3,*, Hisham M. Almongy4

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 353-371, 2021, DOI:10.32604/iasc.2021.017586

    Abstract We introduce a new two-parameter lifetime model, referred to alpha power transformed inverted Topp-Leone, derived by combining the alpha power transformation-G family with the inverted Topp-Leone distribution. Structural properties of the proposed distribution are implemented like; quantile function, residual and reversed residual life, Rényi entropy measure, moments and incomplete moments. The maximum likelihood, weighted least squares, maximum product of spacing, and Bayesian methods of estimation are considered. A simulation study is worked out to evaluate the restricted sample properties of the proposed distribution. Numerical results showed that the Bayesian estimates give more accurate results than the corresponding other estimates in… More >

  • Open Access


    Inference of Truncated Lomax Inverse Lomax Distribution with Applications

    Abdullah Ali H. Ahmadini1, Amal Hassan2, M. Elgarhy3,*, Mahmoud Elsehetry4, Shokrya S. Alshqaq5, Said G. Nassr6

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 199-212, 2021, DOI:10.32604/iasc.2021.017890

    Abstract This paper introduces a modified form of the inverse Lomax distribution which offers more flexibility for modeling lifetime data. The new three-parameter model is provided as a member of the truncated Lomax-G procedure. The new modified distribution is called the truncated Lomax inverse Lomax distribution. The density of the new model can be represented as a linear combination of the inverse Lomax distribution. Expansions for quantile function, moment generating function, probability weighted moments, ordinary moments, incomplete moments, inverse moments, conditional moments, and Rényi entropy measure are investigated. The new distribution is capable of monotonically increasing, decreasing, reversed J-shaped and upside-down… More >

  • Open Access


    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

    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, L-cv, L-variance). Three populations are… More >

  • Open Access


    Kumaraswamy Inverted Topp–Leone Distribution with Applications to COVID-19 Data

    Amal S. Hassan1, Ehab M. Almetwally2,*, Gamal M. Ibrahim3

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 337-358, 2021, DOI:10.32604/cmc.2021.013971

    Abstract In this paper, an attempt is made to discover the distribution of COVID-19 spread in different countries such as; Saudi Arabia, Italy, Argentina and Angola by specifying an optimal statistical distribution for analyzing the mortality rate of COVID-19. A new generalization of the recently inverted Topp Leone distribution, called Kumaraswamy inverted Topp–Leone distribution, is proposed by combining the Kumaraswamy-G family and the inverted Topp–Leone distribution. We initially provide a linear representation of its density function. We give some of its structure properties, such as quantile function, median, moments, incomplete moments, Lorenz and Bonferroni curves, entropies measures and stress-strength reliability. Then,… More >

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