In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

The objective of this research was to investigate the effect of replacing fat(shortening) with different percentages of tahena on the quality properties (physiochemical and sensory ) of shortened cake.The percentages of moisture,protein ,fat and ash of cake increased significantly(p<0.05) as the replacement was increased .The highest increase percentages were 10,48,5,and 90 %,respectivly, at 100% replacement .Carbohydrate,however,decreased by 10%at 100% replacement .these findings may indicate improvement of cake nutritional value.Standing height,as an indicator of cake volume, also increased significantly by 4% at the 50% replacement then it decreased by 4% 100% replacement level. Basic formula (control) has signific

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

This study aimed to show the histological changes that 0ccured in Culex pipiens pipiens larvae and adults infected with Beauveria bassiana . The 4th instar larvae and adult mosquitoes were infected with B.bassiana in 10-4 spore/ml dilution, after 96 hours histological section was studied showing that the fungi infected all the body parts specially Cuticle , Epiderms, fat bodies and midgut. After 120 hours of exposure to the fungi the insect have a white appearance and covered with a thick coat of hyphea. Thus study shows biological control of B .bassiana on mosquitoes.

The preparation of low cost activated carbon from date stones and microwave method by using K₂CO₃ as chemical activator were investigated.

   The prepared activated carbon was used to remove fluoroquinolones antibiotics from aqueous solution. The characterizations of the activated carbon is represented by surface area, pore volume, ash content, moisture content, bulk density, and iodine number. The adsorbed fluoroquinolones antibiotics are Ciprofloxcin (CIP), Norfloxcin (NOR) and Levofloxcin (LEVO). Different variables as pH, initial concentrations and contact time were studied to show the efficieny of prepared activated carbon. The experimental adsorption data were analyzed by Lungmuir, Freundlich

2-(2-amino-5-nitro-phenylazo),-phenol was ready by grouping the diazonium salt of 2-aminophenol with 4-nitroaniline.Thegeometry of azo ligand(HL)was resolved on the origin of (C.H.N) analysis,1H and 13CNMR spectra, infrared spectra and UV–vis electronic absorption spectra. Dealing with the azo ligand produced with Rh+3 and La+3ataqueous ethanol for a 1:3 metal: ligand rate, and in perfect ph. The formation for compounds have been described by utilizing flame atomic, absorption,(C.H.N),Analyses, conductivity, infrared spectra and UV–vis spectral procedures. Nature in the produced compounds, have been studied, obey the ratio of mole and continuous, variance, manners, Beer's law, yielded up a concentration, rate (1×10-4- 3×10-4M),. High