This paper is devoted to compare the performance of non-Bayesian estimators represented by the Maximum likelihood estimator of the scale parameter and reliability function of inverse Rayleigh distribution with Bayesian estimators obtained under two types of loss function specifically; the linear, exponential (LINEX) loss function and Entropy loss function, taking into consideration the informative and non-informative priors. The  performance of such estimators assessed on the basis of mean square error (MSE) criterion. The Monte Carlo simulation experiments are conducted in order to obtain the required results. 

Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their performance is evaluated usin

In this study, a one-dimensional model represented by Butler-Volmer-Monod (BVM) model was proposed to compute the anode overpotential and current density in a mediator-less MFC system. The system was fueled with various organic loadings of real field petroleum refinery oily sludge to optimize the favorable organic loading for biomass to operate the suggested system. The increase in each organic loading showed higher resistance to electrons transport to the anode represented by ohmic loss. On the contrary, both activation and mass transfer losses exhibited a noticeable decrement upon the increased organic loadings. However, current density was improved throughout all increased loads achieving a maximum current density of 5.2 A/m³

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

This research includes the use of CdTe in the design of a solar cell. The SCAPS-1D computer program was used to simulate thin cell capacity of CdTe/CdS by numerical analysis with the addition of a buffer layer (Zn₂SnO₄) to enhance cell efficiency. The thickness of the window layer (n-CdS) was reduced to 25nm with the inclusion of an insulating layer of 50 nm thickness to prevent leakage towards the forward bias with respect to the lower charge carriers. As for the absorber layer thickness (p-CdTe), it varied between 0.5µm and 6µm. The preferable thickness in the absorbent layer was 1.5µm. Different operating temperatures (298K-388K) were used, while the highest conversion efficiency (η=18.43%) was obtain

        A newly developed analytical method was conducted for the determination of Ketotifen fumarate (KTF) in pharmaceuticals drugs via quenching of continuous fluorescence of 9(10H)-Acridone (ACD). The method was applied using flow injection system of a new homemade ISNAG fluorimeter with fluorescence measurements at ± 90◦ via 2×4 solar cell. The calibration graph was linear in the range of 1-45 mmol/L, with correlation coefficient r = 0.9762 and the limit of detection 29.785 µg/sample from the stepwise dilution for the minimum concentration in the linear dynamic ranged of the calibration graph. The method was successfully applied to the determination of Ketotifen fumarate in two different pharma

The concentration of elements were analyzed of twelve cultivation medium (Peat moss, Perlite and Hermon) selected from Iraqi markets using X-ray fluorescence techniques. The analytical results show that the cultivation medium contained high concentration of (Na, Al, Si, S, K, Ca, Fe) and low concentration of (Mg, P, Cl, Ti, V, Cr, Mn, Co, Ni, Cu, Zn). The samples also contained trace concentration of (Ge, As, Se, Br, Sr, Y, Mo, Cd, I, Hg, Pb, U). The results were compared using atomic absorption spectrophotometric technique for measuring the concentration of (K, Ca, Cu, Mn, Zn, Pb).

The Results showed that there is significant difference in the concentration of each element in most of the samples. The concentrations of elements a

Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl^-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their perfor

     The study area is encompassed by the 33.59-34.93°N latitudes and 45.44-46.39°E longitudes and divided into four groups with respect to earthquake event locations. We determined fault plane solutions, moment magnitudes, focal depths, and trend of slip with the direction of the moment stress axes (P, N, and T) for 102 earthquakes. These earthquakes had a local magnitude in the range between 4.0 and 6.4 for the time period from January 2018 to the end of August 2019, with focal depths ranged between 6 and 17 km. Waveform moment tensor inversion technique was used to analyze the database constructed from seismic stations on local and neighboring country networks (Iraq, Iran, and Turkey). We separated the studie

    Osteoarthritis (OA) is a disease of human joints, especially the knee joint, due to significant weight of the body. This disease leads to rupture and degeneration of parts of the cartilage in the knee joint, which causes severe pain. Diagnosis of this disease can be obtained through X-ray. Deep learning has become a popular solution to medical issues due to its fast progress in recent years. This research aims to design and build a classification system to minimize the burden on doctors and help radiologists to assess the severity of the pain, enable them to make an optimal diagnosis and describe the correct treatment. Deep learning-based approaches, such as Convolution Neural Networks (CNNs), have been used to detect knee OA usin