The corrosion behavior of low carbon steel in washing water of crude oil solution has been studied potentiostatically at five temperatures in the range ( 303 –343 )K, at pH ( 4 ) and at pH (4,6,7,9,11 ) at (343K)..The corrosion potential shifted to more negative values with increasing temperature and the corrosion current density increased with increasing temperature, the corrosion current density (icorr) decreased with increasing pH in the rang ( 4 – 7 ) and it increased with increasing pH in the rang ( 9 – 11 ) at ( 343 K ), while the corrosion potential generally variation with increasing pH in the rang (4-11)at(343K. From the general results for this study can be seen that thermodynamic and kinetic function were

The aim of this research is to construct an educational program in light of the theory of behavioral cognitive and its impact on the development of the efficient response to students affected by crises (centers of your right to education). To achieve the objectives of the research, two scales were developed by the researcher in addition to two equivalent hypotheses were formulated. The scale contains (26) items divided into five fields; for its validity and reliability were derived based on the measure of efficient response, an educational program based on the theory of behavioral cognition. The test and the educational program were applied to a sample of (60) students from the centers of your right to education, divided into experimenta

This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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In this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.

Some parameters for advancement of Leishmania tropica infection were examined in three groups of golden hamsters, Group (1) inoculated with autoclaved killed Leishmania tropica , Group (2) inoculated with BCG vaccine alone while Group (3) Inoculated with mixed vaccine (autoclaved killed Leishmania with BCG). The follow up of experimentally infected animals with virulent isolation of Leishmania tropica was done for 90 days, the animals inoculated with mixed vaccine (autoclaved killed Leishmania with BCG) showed the minimum average in each of foot pad thickness (2.3 ± 0.05) mm after (60) days of infection, spleen enlargement (1.13±0.38) after (45) days of infection, spleen length (23.9±0.08) mm after (30) days of infection, liver weight(3.

The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying