In this work we prepared some schiff bases by condensation urea and benzaldehyde or its derevative ( bromo benzaldehyde or hydroxy benzaldehyde ) as ( 1 : 1 ) mole ( urea : benzaldehyde or its substitution ) to prepare compounds ( A1 , B1 , C1 , D1 , E1 , F1 , G1 ) and ( 1 : 2 ) mole ( urea : benzaldehyde or its substitution ) to prepare compounds ( A2 , B2 , C2 , D2 , E1 , F2 , G2 ) . The prepared compounds identified spectroscopic by infrared spectroscopy FT-IR and Thin layer chromotography T.L.C . The force constant calculated from the wave number for the carbonyl stretching from FT-IR chart and by using the following equation K = 4?2C2?'2? The change in double bond order for carbonyl deteremined in according with some past re

In this paper we investigate the use of two types of local search methods (LSM), the Simulated Annealing (SA) and Particle Swarm Optimization (PSO), to solve the problems ( ) and . The results of the two LSMs are compared with the Branch and Bound method and good heuristic methods. This work shows the good performance of SA and PSO compared with the exact and heuristic methods in terms of best solutions and CPU time.

Many oil and gas processes, including oil recovery, oil transportation, and petroleum processing, are negatively impacted by the precipitation and deposition of asphaltene. Screening methods for determining the stability of asphaltenes in crude oil have been developed due to the high cost of remediating asphaltene deposition in crude oil production and processing. The colloidal instability index, the Asphaltene-resin ratio, the De Boer plot, and the modified colloidal instability index were used to predict the stability of asphaltene in crude oil in this study. The screening approaches were investigated in detail, as done for the experimental results obtained from them. The factors regulating the asphaltene precipitation are different fr

Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of  groups based on a linear combination of a set of relevant variables know discriminant function. In this research  discriminant analysis used to analysis data from repeated measurements design. We  will  deal  with the problem of  discrimination  and  classification in the case of  two  groups by assuming the Compound Symmetry covariance structure  under  the  assumption  of  normality for  univariate  repeated measures data.

This article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.

Derivative spectrophotometry is one of the analytical chemistry techniques used
in the analysis and determination of chemicals and pharmaceuticals. This method is
characterized by simplicity, sensitivity and speed. Derivative of Spectra conducted
in several ways, including optical, electronic and mathematical. This operation
usually be done within spectrophotometer. The paper is based on form of a new
program. The program construction is written in Visual Basic language within
Microsoft Excel. The program is able to transform the first, second, third and fourth
derivatives of data and the return of these derivatives to zero order (normal plot).
The program was applied on experimental (trial) and reals values of su

The integral  breadth  method  has been utilized to analyse line

proIiles broadening and lattice strain of CaO at different temperatures

The effect of tcmperattre on crystallite size and strain has also been investigated  . The crystall i tes are found to be highly anisotropic even at high temperatures

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The present research aims to present a theoretical framework for the application of takaful insurance in Iraq, as well as to identify the level of impact on the development of insurance services in the Iraqi market, and to make recommendations and suggestions that lead to increased interest in this area, and thus contribute to the development and integration of insurance service in the Iraqi market,

The research adopted the descriptive analytical method, and the questionnaire was used to survey the opinions of the research sample consisting of department managers and their assistants and some employees of the graduate degrees in addition to employees of the departments of electronic calculator in the Iraqi insurance sector, and t