This study was aimed to investigate the load of bacterial contaminant in fresh meat with different types of bacteria.One handered and seven samples were collected from different regions of Baghdad . These samples included 37 of fresh beef 70 of fresh sheep meat. All samples were cultured on different selective media to identitfy of contaminated bacteria .The result revealed that The percentage of bacterial isolate from raw sheep meat were, % 23.8of StreptococcusgroupD,29.4 % of Staphylococcus aureus ,14.7 % of E.coli , %4.9of Salmonella spp, ,%3.5 of pseudomonas aeruginosa, %14.7.%14.7 of Proteus spp.% 2.1 of Listeria spp while the raw beef meat content %5.55 of Staphylococcus aureus, %8.14 of streptococcus group D , %5.18 %1.85 of E.coli,%3.7 of Proteus spp ،%1.85of Salmonella spp 1.85 % of pseudomonas aeruginosa، . % 1.48 of Bacillus cereus and.1.48 % of Klebsiella spp
This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett
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In this paper, a subspace identification method for bilinear systems is used . Wherein a " three-block " and " four-block " subspace algorithms are used. In this algorithms the input signal to the system does not have to be white . Simulation of these algorithms shows that the " four-block " gives fast convergence and the dimensions of the matrices involved are significantly smaller so that the computational complexity is lower as a comparison with " three-block " algorithm .
Background: Reliable detection the etiological agent of amoebic dysentery and extra-intestinal amoebiasis have Public health importance specially in asymptomatic human and animals, Since the acquisition of pet dogs in the recent period has become widespread in our city. Aim: To give correct perception of infection rate in asymptomatic individuals (human and domestic dogs) for the first aspect and about detection and diagnosis of the pathogenic species of Entamoeba histolytica from another morphologically similar and commensal one using the molecular technique in stool samples of asymptomatic individuals the second aspect. Methods: During the study period from the beginning of September 2020 to the end of February 2021, a total of 95 stool s
... Show MoreThe use of deep learning.
New speaker identification test’s feature, extracted from the differentiated form of the wave file, is presented. Differentiation operation is performed by an operator similar to the Laplacian operator. From the differentiated record’s, two parametric measures have been extracted and used as identifiers for the speaker; i.e. mean-value and number of zero-crossing points.
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The purified prepared compounds were identified through different methods of identification i.e, I.R, UV-vi^ble-spectroscopy in addition to (coloured tests) Calculation of the sum of OH groups. TLC techniques were also used to test the purity and the speed ofthe rate of flow (RF).