Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

Apparent molar volume, V?, and viscosity B-coefficient of nicotinc acid in water and in aqueous NaCl solutions have been determined from density and viscosity measurements at (293.15, 298.15, 303.15 and 308.15) K. The experimental density data were evaluated by Masson equation, and the derived, apparent molar volume at infinite dilution, Vo?, and the slope Sv, were interpreted in term of solute-solvent and solute- solute interactions. Transfer apparent molar volumes at infinite dilution of nicotinic acid from water to NaCl solutions at various temperatures have been calculated.The viscosity data have been analyzed using Jones-Dole equation, and the derived parameters, Jones-Dolecoefficient, B,and Falkenhagen coefficient,A, have been also in

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

 This paper devoted to the analysis of regular singular boundary value problems for ordinary differential equations with a singularity of the different kind , we propose semi - analytic technique using two point osculatory interpolation to construct polynomial solution, and discussion behavior of the solution in the neighborhood of the regular singular points and its numerical approximation. Many examples are presented to demonstrate the applicability and efficiency of the methods. Finally , we discuss behavior of the solution in the neighborhood of the singularity point which appears to perform satisfactorily for singular problems.

Transport is a problem and one of the most important mathematical methods that help in making the right decision for the transfer of goods from sources of supply to demand centers and the lowest possible costs, In this research, the mathematical model of the three-dimensional transport problem in which the transport of goods is not homogeneous was constructed. The simplex programming method was used to solve the problem of transporting the three food products (rice, oil, paste) from warehouses to the student areas in Baghdad, This model proved its efficiency in reducing the total transport costs of the three products. After the model was solved in (Winqsb) program, the results showed that the total cost of transportation is (269,

   In this paper we introduce many different Methods of ridge regression to solve multicollinearity problem in linear regression model. These Methods include two types of ordinary ridge regression (ORR1), (ORR2) according to the choice of ridge parameter as well as generalized ridge regression (GRR). These methods were applied on a dataset suffers from a high degree of multicollinearity, then according to the criterion of mean square error (MSE) and coefficient of determination (R2) it was found that (GRR) method performs better than the other two methods.