When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every

Chronic myeloid leukemia (CML) is a myeloproliferative disorder characterized by the presence Philadelphia chromosome (Ph) which was created by a reciprocal translocation between chromosomes 9 and 22 (t [9;22] [q34;q11]. The approval of the 2nd generation TKI ( Nilotinib) takes the treatment of CML patients into new erea with more efficiency and mild to moderate adverse effects. This study was aimed at evaluation of molecular cytogenetic response by (FISH) for Nilotinib in Iraqi patients with assessment for electrolytes disturbances of Nilotinb by measuring a panel of electrolyte (Na+, K+, Ca++, PO4--- and Mg++) , where thirty Iraqi patients with CML who have resistance or no response to Imatinib treatment, attending to Baghdad Teaching Ho

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

Human beings are starting to benefit from the technology revolution that witness in our time. Where most researchers are trying to apply modern sciences in different areas of life to catch up on the benefits of these technologies. The field of artificial intelligence is one of the sciences that simulate the human mind, and its applications have invaded human life. The sports field is one of the areas that artificial intelligence has been introduced. In this paper, artificial intelligence technology Fast-DTW (Fast-Dynamic Time Warping) algorithm was used to assess the skill performance of some karate skills. The results were shown that the percentage of improvement in the skill performance of Mai Geri is 100%.

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

This work deals with preparation of Sulfated Zirconia catalyst (SZ) for isomerization of n-hexane model and refinery light naphtha, as well as enhanced the role of promoters to get the target with the mild condition, stability, and to prevent formation of coke precursors on strong acidic sites of the catalyst. The prepared SZ catalysts were characterization by fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Brunauer –Emmett-Teller (BET) surface area analysis, Thermogravimetric Analysis (TGA), Scanning Electron Microscope (SEM) and atomic force microscopy (AFM) Analyzer. The results illustrate that the maximum conversion and selectivity for n-hexane isomerization with Ni-WSZ and operating temperature of 150 °C