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.

Joint diseases, such as osteoarthritis, induce pain and loss of mobility to millions of people around the world. Current clinical methods for the diagnosis of osteoarthritis include X-ray, magnetic resonance imaging, and arthroscopy. These methods may be insensitive to the earliest signs of osteoarthritis. This study investigates a new procedure that was developed and validated numerically for use in the evaluation of cartilage quality. This finite element model of the human articular cartilage could be helpful in providing insight into mechanisms of injury, effects of treatment, and the role of mechanical factors in degenerative
conditions, this three-dimensional finite element model is a useful tool for understanding of the stress d

     Lately, a growing interest has been emerging in age estimation from face images because of the wide range of potential implementations in law enforcement, security control, and human computer interactions. Nevertheless, in spite of the advances in age estimation, it is still a challenging issue. This is due to the fact that face aging process is not only set by distinct elements, such as genetic factors, but by extrinsic factors, such as lifestyle, expressions, and environment as well. This paper applied machine learning technique to intelligent age estimation from facial images using J48 classifier on FG_NET dataset. The proposed work consists of three phases; the first phase is image preprocessing which include

    The relationship between prey and predator populations is hypothesized and examined using a mathematical model. Predation fear, cannibalism among the prey population, and a refuge reliant on predators are predicted to occur. This study set out to look at the long-term behavior of the proposed model and the effects of its key elements. The solution properties of the model were investigated. All potential equilibrium points' existence and stability were looked at. The system's persistence requirements were established. What circumstances could lead to local bifurcation near equilibrium points was uncovered. Suitable Lyapunov functions are used to study the system's overall dynamics. Numerical simulations were conducted to verify the

This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to

      Multiple sclerosis (MS) is one of an autoimmune condition with uncertain etiopathology. According to new data, ABO system had played a role in the development and understanding numerous diseases. Lower level of 25-hydroxy vitamin D3 (25-OHD3) is considered as a risk factor for MS. The aims of this study is to identify the role of blood group distribution on the levels of parathyroid hormone (PTH), 25-OHD3, total calcium, inorganic phosphorus and total magnesium on MS patients. Additionally, we assessed the relation between Expanded Disability Status Scale (EDSS) and study parameters in patients. The Study included 107 patients with MS were distributed in to four groups according to their blood group (A, B, AB, and O).  Additi

     Ground penetrating radar (GPR) technology is used to determine the extent to which this technique can detect with a high-frequency range from 10 MHz to 1000 MHz into the ground by a transmitting antenna and A graveyard was found beneath the depth of the three meters under Surface of the earth in the shrine of the Prophet Houd and Saleh in Al-Najaf Governorate surveyed by through 4 tracks. Ground Penetrating Radar (GPR) is a device that transmits short pulses of electromagnetic energy with pulse duration about 1 ns to 20 ns. applying the filter Time- Zero to the same profile at a depth (3m) , Two types of antennas were used in this study, with two different frequencies antennas (250, 500 )MHz Three tracks (23,25,2

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope