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  • Open Access

    ARTICLE

    Designing Bayesian Two-Sided Group Chain Sampling Plan for Gamma Prior Distribution

    Waqar Hafeez1, Nazrina Aziz1,2,*

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1069-1079, 2023, DOI:10.32604/csse.2023.022047 - 15 June 2022

    Abstract Acceptance sampling is used to decide either the whole lot will be accepted or rejected, based on inspection of randomly sampled items from the same lot. As an alternative to traditional sampling plans, it is possible to use Bayesian approaches using previous knowledge on process variation. This study presents a Bayesian two-sided group chain sampling plan (BTSGChSP) by using various combinations of design parameters. In BTSGChSP, inspection is based on preceding as well as succeeding lots. Poisson function is used to derive the probability of lot acceptance based on defective and non-defective products. Gamma distribution… More >

  • Open Access

    ARTICLE

    Properties of Certain Subclasses of Analytic Functions Involving q-Poisson Distribution

    Bilal Khan1,*, Zhi-Guo Liu1, Nazar Khan2, Aftab Hussain3, Nasir Khan4, Muhammad Tahir2

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1465-1477, 2022, DOI:10.32604/cmes.2022.016940 - 19 April 2022

    Abstract By using the basic (or q)-Calculus many subclasses of analytic and univalent functions have been generalized and studied from different viewpoints and perspectives. In this paper, we aim to define certain new subclasses of an analytic function. We then give necessary and sufficient conditions for each of the defined function classes. We also study necessary and sufficient conditions for a function whose coefficients are probabilities of q-Poisson distribution. To validate our results, some known consequences are also given in the form of Remarks and Corollaries. More >

  • Open Access

    ARTICLE

    Adaptive Multi-Cost Routing Protocol to Enhance Lifetime for Wireless Body Area Network

    Muhammad Mateen Yaqoob1, Waqar Khurshid1, Leo Liu2, Syed Zulqarnain Arif1, Imran Ali Khan1, Osman Khalid1,*, Raheel Nawaz2

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1089-1103, 2022, DOI:10.32604/cmc.2022.024798 - 24 February 2022

    Abstract Wireless Body Area Network (WBAN) technologies are emerging with extensive applications in several domains. Health is a fascinating domain of WBAN for smart monitoring of a patient's condition. An important factor to consider in WBAN is a node's lifetime. Improving the lifetime of nodes is critical to address many issues, such as utility and reliability. Existing routing protocols have addressed the energy conservation problem but considered only a few parameters, thus affecting their performance. Moreover, most of the existing schemes did not consider traffic prioritization which is critical in WBANs. In this paper, an adaptive More >

  • Open Access

    ARTICLE

    An Intelligent Fine-Tuned Forecasting Technique for Covid-19 Prediction Using Neuralprophet Model

    Savita Khurana1, Gaurav Sharma2, Neha Miglani3, Aman Singh4, Abdullah Alharbi5, Wael Alosaimi5, Hashem Alyami6, Nitin Goyal7,*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 629-649, 2022, DOI:10.32604/cmc.2022.021884 - 03 November 2021

    Abstract COVID-19, being the virus of fear and anxiety, is one of the most recent and emergent of various respiratory disorders. It is similar to the MERS-COV and SARS-COV, the viruses that affected a large population of different countries in the year 2012 and 2002, respectively. Various standard models have been used for COVID-19 epidemic prediction but they suffered from low accuracy due to lesser data availability and a high level of uncertainty. The proposed approach used a machine learning-based time-series Facebook NeuralProphet model for prediction of the number of death as well as confirmed cases… More >

  • Open Access

    ARTICLE

    Bayesian Group Chain Sampling Plan for Poisson Distribution with Gamma Prior

    Waqar Hafeez1, Nazrina Aziz1,2,*, Zakiyah Zain1,2, Nur Azulia Kamarudin1

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3891-3902, 2022, DOI:10.32604/cmc.2022.019695 - 27 September 2021

    Abstract Acceptance sampling is a statistical quality control technique that consists of procedures for sentencing one or more incoming lots of finished products. Acceptance or rejection is based on the inspection of sampled products drawn randomly from the lot. The theory of previous acceptance sampling was built upon the assumption that the process from which the lots are produced is stable and the process fraction nonconforming is a constant. Process variability is inevitable due to random fluctuations, which may inadvertently lead to quality variation. As an alternative to traditional sampling plans, Bayesian approach can be used… More >

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