In this research, the semiparametric Bayesian method is compared with the classical  method to  estimate reliability function of three  systems :  k-out of-n system, series system, and parallel system. Each system consists of three components, the first one represents the composite parametric in which failure times distributed as exponential, whereas the second and the third components are nonparametric ones in which reliability estimations depend on Kernel method using two methods to estimate bandwidth parameter h method and Kaplan-Meier method. To indicate a better method for system reliability function estimation, it has be

The present study focuses on the deformation of neutron-rich nuclei near the neutron drip line. The nuclei of interest include 28O, 42Si, 58Ca, 80Ni, 100Kr, 122Ru, 152Ba, 166Sm, and 176Er. The relativistic Hartree - Bogoliubov (RHB) approach with effective density-dependent point coupling is utilized to investigate the triaxial deformation, and Skyrme - Hartree - Fock + Bardeen - Cooper - Schrieffer is used to analyze the axial deformation. The study aimed to understand the interplay between nuclear forces, particle interactions, and shell structure to gain insights into the unique behavior of neutron-rich nuclei. Despite these nuclei containing magic numbers, their shapes are still affected by the nucleons' collective behavior and

In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

Foreign body embolization is a rare but serious iatrogenic complication that might necessitate transcatheter or even surgical retrieval. A broken double-lumen catheter was snared using a goose neck snare kit. The procedure was successful, and the patient experienced no further complications.

This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

The effect of some environmental factors in the loss rate for high weights virgins are full to the screwworm fly of the ancient world and included temperatures 15,20,25,30,35,40 study showed that the rate of loss in weight virgins advanced to full participants at a temperature of 15 C while notgets evolution

The demand for single photon sources in quantum key distribution (QKD) systems has necessitated the use of weak coherent pulses (WCPs) characterized by a Poissonian distribution. Ensuring security against eavesdropping attacks requires keeping the mean photon number (µ) small and known to legitimate partners. However, accurately determining µ poses challenges due to discrepancies between theoretical calculations and practical implementation. This paper introduces two experiments. The first experiment involves theoretical calculations of µ using several filters to generate the WCPs. The second experiment utilizes a variable attenuator to generate the WCPs, and the value of µ was estimated from the photons detected by the BB