Cupressus sempervirens L., Cupressaceae, that is known as evergreen cypress, Mediterranean cypress and in Arabic called “al -Sarw. It is an evergreen, medium sized, longevity, and wide distributed over all the world. The plant represents an important member of conifer plants which characterized with aromatic leaves and cones. Cupressus sempervirens have been ethnobotanical uses as an antiseptic, relief of cough, astringent, antispasmodic, wound healing and anti-inflammatory. Aims of this work are phytochemical analysis, isolation and structural identification of Quercitroside (quercitrin) and essential oil in Iraqi C. sempervirens. Isolation of quercitrin was

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For

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

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

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

The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlatio

In this work magnetite/geopolymer composite (MGP) were synthesized using a chemical co-precipitation technique. The synthesized materials were characterized using several techniques such as: “X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), vibrating sample-magnetometer (VSM), field-emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), Brunauer–Emmett–Teller (BET) and Barrentt-Joyner-Halenda (BJH)” to determine the structure and morphology of the obtained material. The analysis indicated that metal oxide predominantly appeared at the shape of the spinel structure of magnetite, and that the presence of nano-magnetite had a substantial impact on the surface area and pore st

A field experiment was conducted at the field of the Dept. of Field Crop Sci. / College of Agriculture / University of Baghdad . The objective was to determine the values of relative constant of three – way and double crosses of maize . Ten inbreds were used and crossed during spring and fall seasons of 2009 to produce three - way and double crosses , and ten hybrids were taken from each group . The ten hybrids were grown and selfed during spring 2010 to produce 2 seed . Three way and double crosses were sown with their parents and 2 seed during fall 2010 in RCBD with four replicates . Leaf area , total dry matter , row/ear , grain/ear , grain weight and grain weight/plant of hybrids , parents and 2 plants were taken . Results showed that

A new Schiffbase derivative ligands [H4L1] and [H2L2] have been produced by condensed ophathaldehyde with ethylene diamine and [N1, N1'E, N1, N1'E)-N1, N1'-(1, 2-phenylenebis (methan-1-yl- 1ylidene)) diethane-1, 2-diamine] with 2-benzoyl benzoic acid. Schiffbase ligands have been separated and categorized by 1H, 13 C-NMR, (CHN) elemental analysis, UV-visible, mass spectroscopy and FTIR methods. Ten new coordination complexes were prepared and structurally diagnosed: [M(L1)Cl2] and [M2(L2)Cl2] where M(II) = Mn (II), Co(II), Ni(II), Cu(II) and Hg(II). The complexes have been typified by FTIR, UV-visble atomic absorption, molar conductance elemental analysis, and magnetic susceptibility. The details of the ligand (H4L1) compounds are getting a