A series of experiments were conducted for the first time in Iraq to evaluate the efficiency of five plant leaves extracts (Ibicella lutea, Nerium oleander, Clerodendron inerme, Allium cepa and Eucalyptus spp.) in treating the common carp (Cyprinus carpio) infected with monogenetic trematodes of genera Dactylogyrus. Five different concentrations of such extracts were used to bathe fishes for 5,10,15,20 and 25 minutes. A concentration of 15% A. cepa for 25 minutes of bath exposure was affective in trematode eradication. Extracts of both Eucalyptus and N. oleander at a concentration of 10% each were also affective for ten minutes exposure. Extracts of C. inerme had no any effect on such parasites. On the otherhand, extracts of 1. hitea caused

Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f

The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A

Background: preparation of root canals is an important step in root canal treatment. Mechanical instrumentation of root canals cause an irregular layer of debris, known as the smear layer. As a result, several studies reported that preferring the removal of the smear layer. Objective: To study the influence of the energy (100 mJ) of Erbium, Chromium: Yttrium Scandium Gallium Garnet (Er,Cr:YSGG) laser at short pulse duration (60 μs)  on smear layer removal of apical third after using Photon induced photoacoustic streaming technique. Materials and methods: Eighteen straight single-rooted mandibular premolars were used. The roots length were uniform to 14mm from the anatomic apex and

The present research was conducted to reduce the sulfur content of Iraqi heavy naphtha by adsorption using different metals oxides over Y-Zeolite. The Y-Zeolite was synthesized by a sol-gel technique. The average size of zeolite was 92.39 nm, surface area 558 m²/g, and pore volume 0.231 cm³/g. The metals of nickel, zinc, and copper were dispersed by an impregnation method to prepare Ni/HY, Zn/HY, Cu/HY, and Ni + Zn /HY catalysts for desulfurization. The adsorptive desulfurization was carried out in a batch mode at different operating conditions such as mixing time (10,15,30,60, and 600 min) and catalyst dosage (0.2,0.4,0.6,0.8,1, and 1.2 g). The most of the sulfur compounds were removed at 10 min for all catalyst ty

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

S Khalifa E, N Adil A, AS Mazin M…, 2008