This research work aims to the determination of molybdenum (VI) ion via the formation of peroxy molybdenum compounds which has red-brown colour with absorbance wave length at 455nm for the system of ammonia solution-hydrogen peroxide-molybdenum (VI) using a completely newly developed microphotometer based on the ON-Line measurement. Variation of responses expressed in millivolt. A correlation coefficient of 0.9925 for the range of 2.5-150 ?g.ml-1 with percentage linearity of 98.50%. A detection limit of 0.25 ?g.ml-1 was obtained. All physical and chemical variable were optimized interferences of cation and anion were studied classical method of measurement were done and compared well with newly on-line measurements. Application for the use

The objective of present study was to investigate the effect of using duplex volaticle oil of Rosmarinusoficinolis and Nigella sativain microbial quality, sensing and extending storage time of minced cold poultry meat. Duplex volaticle oil was added at 25, 50 and 75 mg/kg to minced poultry meat , these treatments were stored individually for (0 ,4 and 7) days at( 4-7) C0 . After making several microbial and sensing test. The following results were obtained:- The process of adding duplex volaticle oil of Rosmarinus officinolis and Nigella sativa to minced poultry meat led to significant reduced (P<0.01) in total arobic count, psychrophilic count and coliform bacteria during refrigerated storage periods. The results showed asignificant sens

methodology six sigma Help  to reduce defects by solving problems effectively, and works Lean to reduce losses through the flow of the manufacturing process and when integrating these two methodologies (Lean and six sigma), the methodology of Lean six sigma will form the entrance to the organizers of the optimization process and increase the quality and reduce lead times and costs . by focusing on the needs of the customer. this process uses statistical tools and techniques to analyze and improve processes.

 We have conducted this research in the General Company for Electrical Industries and adopted its product (machine cooling water three taps) as a sample for research. In order to determine t

Coupling reaction of ( 4-amino antipyrene) with the (L- tyrosine ) gave the new azo ligand 2- ( 4- Antipyrene azo ) - tyrosine .Treatment of this ligand with metal ions (Mn(II) ,Co(II), Ni(II), and Cu(II) )in ethanolic medium in (1:2) (M:L) ratio yield a series of a neutral complexes of the general formula [M(L)2] . The prepared complexes were characterized using flame atomic absorption , FT.IR , UV-Vis spectroscopic and elemental microanalysis (C.H.N) as well as magnetic susceptibility and conductivity measurement

This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,

In this paper , an efficient new procedure is proposed to modify third –order iterative method obtained by Rostom and Fuad [Saeed. R. K. and Khthr. F.W. New third –order iterative method for solving nonlinear equations. J. Appl. Sci .7(2011): 916-921] , using three steps based on Newton equation , finite difference method and linear interpolation. Analysis of convergence is given to show the efficiency and the performance of the new method for solving nonlinear equations. The efficiency of the new method is demonstrated by numerical examples.

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security