A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

In the present study waste aluminium cans were recycled and converted to produce alumina catalyst. These cans contain more than 98% aluminum oxide in their structure and were successfully synthesized to produce nano sized gamma alumina under mild conditions. A comprehensive study was carried out in order to examine the effect of several important parameters on maximum yield of alumina that can be produced. These parameters were reactants mole ratios (1.5, 1.5, 2, 3, 4 and 5), sodium hydroxide concentrations (10, 20, 30, 40, 50 and 55%) and weights of aluminum cans (2, 4, 6, 8 and 10 g). The compositions of alumina solution were determined by Atomic absorption spectroscopy (AAS); and maximum yield of alumina solution was 96.3% obtain

     The Zubair Formation is one of the major reservoirs of high production in the Rumaila oilfield, southern Iraq. The petrophysical properties analysis of the Upper Sand Member (Main Pay) of the Zubair Formation was conducted. The study includes results analysis of four wells distributed along the South Rumaila oilfield. Using a set of open well-logs, the main pay was divided into three main pay (AB, DJ and LN) units separated by two insulating shale units (C and K). The unit DJ was subdivided into three secondary reservoir units: D, F, H and the LN unit, which is split into L, M, and N. The research also includes the statistical analysis of the petrophysical properties, the calculation of the heterogeneity of the reservoir, and th

     The inorganic phosphate content and antioxidant activity of fresh fruit juices and canned fruit juices commonly consumed in Bahrain were compared. The fruits considered in this study were kiwi, guava, black grape, strawberry, apple, and pineapple. The inorganic phosphate content of the juices was determined by a colorimetric method using a UV/VIS spectrophotometer. Among the fresh juices, the highest inorganic phosphate content was measured for black grape juice (17.330 ±0.068 mg/L), and among the canned juices, the highest inorganic phosphate was measured for black grape canned juice too (16.020 ±0.141 mg/L, brand 3). The antioxidant activity was determined in-vitro by measuring the percentage of 2,2-diphenyl-1-picrylhydrazyl

In this paper, we propose new types of non-convex functions called strongly --vex functions and semi strongly --vex functions. We study some properties of these proposed functions. As an application of these functions in optimization problems, we discuss some optimality properties of the generalized nonlinear optimization problem for which we use, as an objective function, strongly --vex function and semi strongly --vex function.

      In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space. The trained networks are then used in an conjugate gradient algorithm to estimate the output. These neural networks are then applied to solve differential equation. Results of applying these algorithms to several examples are presented

In this paper, we proposed to zoom Volterra equations system Altfazlah linear complementarity of the first type in this approximation were first forming functions notch Baschtdam matrix and then we discussed the approach and stability, to notch functions