Research Hypothesis from the fact that kicks off the effect that agricultural production in Iraq plays an important role in overcoming the food problem and achieving food security, but he became far far away from the provision of sufficient quantities of food products and then securing the Iraqi consumer food basket by the challenges faced by the agricultural sector.
To prove the hypothesis research in its structure in three axes came, the first axis eating historical significance to the subject of food over time periods as well as to clarify the concept of food security, and the second axis touched on the most important challenges facing the agricultural sector in Iraq and prevent the achievement of food requirements for members of

The data preprocessing step is an important step in web usage mining because of the nature of log data, which are heterogeneous, unstructured, and noisy. Given the scalability and efficiency of algorithms in pattern discovery, a preprocessing step must be applied. In this study, the sequential methodologies utilized in the preprocessing of data from web server logs, with an emphasis on sub-phases, such as session identification, user identification, and data cleansing, are comprehensively evaluated and meticulously examined.

This study was conducted in the poultry field of the College of Agricultural Engineering Sciences / University of Baghdad for the period from 10/15/2021 to 11/25/2021 in order to show the effect of adding different levels of Ganoderma lucidum to broiler diets on physiological traits and indicators of fat oxidation in meat. In it, 200 unsexed (Ross 308) chicks of one-day-old breed were used, with a starting weight of (40) g. The chicks were distributed and randomly divided into four treatments, with 50 birds for each treatment. One treatment included five replicates (10 birds/repeat) and the experiment treatments were T1, T2, T3, and T4. The percentages of adding reishi mushrooms were 0, 0.5, 1, and 1.5 g/kg of feed, respectively. Th

Pregnant women who have rubella may potentially pass the infection on to their unborn offspring. A congenital rubella infection can result in a miscarriage, stillbirth, and congenital rubella syndrome. The only member of the Togaviridae family’s Rubivirus genus, the Rubella virus (RV) is a positive-polarity, single-stranded RNA virus genome surrounded by a lipoprotein envelope with spike-like, hemagglutinin-containing surface projections.The objective: to determine the Rubella virus (1E genotype) in pregnant woman and its relation to spontaneous miscarriage.Materials and methods. A total of 174 women which visited Al-Elweya Teaching Hospital, Baghdad, Iraq, were screened according to the following criteria: women with a history of

The current study focuses on the bacterium Acinetobacter baumannii due to its importance as a nosocomial infections source in addition to its increased resistance against antibiotics. Different clinical and hospital environment samples were collected, and cultured on A. baumannii selective media: Leed Acinetobacter agar and Herellea agar. A. baumannii have been identified by traditional methods, followed by confirmation using molecular identification to detect bla_{oxa-51 like} gene which is considered a diagnostic gene since it is present in genome of all A. baumannii strains. The result was, nineteen bacterial isolates of A.baumannii were obtained, from twenty-seven suspected isolate

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func