G. Bhargavi^*, J. Arunnehru

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1257-1272, 2023, DOI:10.32604/iasc.2023.034335

Abstract Landslides are a natural hazard that is unpredictable, but we can prevent them. The Landslide Susceptibility Index reduces the uncertainty of living with landslides significantly. Planning and managing landslide-prone areas is critical. Using the most optimistic deep neural network techniques, the proposed work classifies and analyses the severity of the landslide. The selected experimental study area is Kerala’s Idukki district. A total of 3363 points were considered for this experiment using historic landslide points, field surveys, and literature searches. The primary triggering factors slope degree, slope aspect, elevation (altitude), normalized difference vegetation index (NDVI), and distance from road, lithology, and… More >

Amer I. Al-Omari¹, Amal S. Hassan², Heba F. Nagy², Ayed R. A. Al-Anzi^3,*, Loai Alzoubi¹

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3795-3811, 2021, DOI:10.32604/cmc.2021.019061

Abstract This paper deals with the Bayesian estimation of Shannon entropy for the generalized inverse exponential distribution. Assuming that the observed samples are taken from the upper record ranked set sampling (URRSS) and upper record values (URV) schemes. Formulas of Bayesian estimators are derived depending on a gamma prior distribution considering the squared error, linear exponential and precautionary loss functions, in addition, we obtain Bayesian credible intervals. The random-walk Metropolis-Hastings algorithm is handled to generate Markov chain Monte Carlo samples from the posterior distribution. Then, the behavior of the estimates is examined at various record values. The output of the study… More >

Sk Sarif Hassan¹, Ranjeet Kumar Rout², Kshira Sagar Sahoo³, Nz Jhanjhi⁴, Saiyed Umer⁵, Thamer A. Tabbakh^6,*, Zahrah A. Almusaylim⁷

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3477-3493, 2021, DOI:10.32604/cmc.2021.017206

Abstract Coronaviruses are responsible for various diseases ranging from the common cold to severe infections like the Middle East syndromes and the severe acute respiratory syndrome. However, a new coronavirus strain known as COVID-19 developed into a pandemic resulting in an ongoing global public health crisis. Therefore, there is a need to understand the genomic transformations that occur within this family of viruses in order to limit disease spread and develop new therapeutic targets. The nucleotide sequences of SARS-CoV-2 are consist of several bases. These bases can be classified into purines and pyrimidines according to their chemical composition. Purines include adenine… More >

Ibrahim M. Almanjahie^1,2,*, Javid Gani Dar³, Amer Ibrahim Al-Omari⁴, Aijaz Mir⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 907-925, 2021, DOI:10.32604/cmes.2021.014896

Abstract Many researchers measure the uncertainty of a random variable using quantile-based entropy techniques. These techniques are useful in engineering applications and have some exceptional characteristics than their distribution function method. Considering order statistics, the key focus of this article is to propose new quantile-based Mathai-Haubold entropy and investigate its characteristics. The divergence measure of the Mathai-Haubold is also considered and some of its properties are established. Further, based on order statistics, we propose the residual entropy of the quantile-based Mathai-Haubold and some of its property results are proved. The performance of the proposed quantile-based Mathai-Haubold entropy is investigated by simulation… More >