This research has been prepared to isolate and diagnose one of the most important vegetable oils from the plant medical clove is the famous with Alaeugenol oil and used in many pharmaceuticals were the isolation process using a technique ultrasonic extraction and distillation technology simple

Regression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well-  Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.

Paper type:

   AlPO₄ solid acid catalyst was prepared in order to use it in transesterification reaction of edible oil after supporting it with tungsten oxide. The maximum conversion of edible oil was obtained 78.78% at catalyst concentration (5gm.), temperature 70°Ϲ, 30/1 methanol/edible oil molar ratio, and time 5hr. The study of kinetics of the transesterification reaction of edible oil indicates that the reaction has an order of 3/2, while the value of activation energy for  transesterification reaction is 51.367 kJ/mole and frequency factor equal 26219.13(L/ mol.minute).

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

This study is aimed to use the aerobic packed bed in biotreatment of the wastewater which is discharge from AL-KARAMA teaching hospital in Baghdad. The performance of packed-bed treatment method was examined for elimination of the organic compounds from wastewater under aerobic conditions. In this research different parameters were studied. They were: inoculums concentration, circulation rate of wastewater through the bed, packing type and the temperature. Results showed that the system efficiently removed about 82% of the chemical oxygen demand (COD) and 80% of the Biological oxygen demand (BOD). Percent reduction in turbidity was about 92% and reduction in nitrate concentration was about 87%. It was found that best performance of the pack

The present study examines the extraction of lead (Pb), cadmium (Cd) and nickel (Ni) from   a contaminated soil by washing process. Ethylenediaminetetraacetic acid disodium salt (Na₂EDTA) and hydrochloric acid (HCl) solution were used as extractants.  Soil washing is one of the most suitable in-situ/ ex-situ remediation method in removing heavy metals. Soil was artificially contaminated with 500 mg/kg (Pb , Cd and Ni ).  A set of batch experiments were carried out at different conditions of  extractant concentration , contact time, pH and agitation speed. The results  showed  that the  maximum removal efficiencies  of (Cd, Pb  and Ni ) were (97, 88 and 24 )&nbs

This study employed the biosynthetic technique for creating vanadium nanoparticles (VNPs), which are affordable and user-friendly; VNPs was synthesized using vanadium sulfate (VOSO4.H2O) and a plant extract derived from Fumaria Strumii Opiz (E2) at a NaOH concentration of 0.1 M. This study aims to investigate the potential applications of utilizing an adsorbent for metal ions to achieve environmentally friendly production and assess its antibacterial activity and cytotoxicity. The reaction was conducted in an alkaline environment with a pH range of 8–12. The resulting product was subjected to various characterization techniques, including Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, x-ray diffraction (XRD), t

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes