The study aimed to assess Milk Thistle oi reducing the aflatoxin damage and improve the health status of local breed hens. The study was performed on 60 hens aged 35 weeks, weighing 2-2.5 kg of the body was obtained and housed on a private poultry farm in north of Baghdad (Altaji) for a period of 9 weeks from 22 October until 22 December 2020. Hens were divided to three treatments (20 hens). The first was fed a basal diet free of aflatoxin. The 2nd fed on a contaminated diet with aflatoxin (14.6 ppb) while the 3rd fed as in the 2nd with 0.5% of Milk Thistle oil /kg feed. A 5 hens from each group were slaughtered at the end of the trial for the histopathological inspection of liver, spleen and intestine tissues to evaluate the harmfu

Rutting is one of the major distresses in pavement. The objective of this paper is to develop an improved asphalt binder grading system for Iraq based on the principal of Superpave system, and increasing performance grade of product asphalt binder in Iraq using polymers without raising the viscosity of the binder. Two types of polymers are used, Plastomers, Functionalized Polyethylene (PE) which is developed by asphalt research group in Wisconsin University in the USA, and Elastomers, Styrene Butadiene Styrene (SBS) with and without cross linker. Mastercurve are drown for these modified binders, Rolling thin film aged, to show effects on rheological properties at high temperature for complex modulus (G*) and phas

Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different

The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi

There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

ABSTRACT

The research aims to study the effect of the commodity dumping phenomenon that Iraq suffered after 2003 on the consumption pattern of individuals, towards the acquisition of non-essential goods (luxury). To achieve our goal we relied on the questionnaire as a main tool for obtaining information related to the research, and it was distributed on a random sample of consumers in the city of Baghdad with 250 questionnaires. The answers of the research sample were analyzed using the statistical program (SPSS). The percentage weights and the factorial analysis method were used also to arrange the variables that affected on changing consumption patterns. The research reached a set of conclusions:

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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co