Simple, economic and sensitive mathematical spectrophotometric methods were developed for the estimation 4-aminoantipyrine in presence of its acidic product. The estimation of binary mixture 4-aminoantipyrine and its acidic product was achieved by first derivative and second derivative spectrophotometric methods by applying zero-crossing at (valley 255.9nm and 234.5nm) for 4-aminoantipyrine and (peak 243.3 nm and 227.3nm) for acidic product. The value of coefficient of determination for the liner graphs were not less than 0.996 and the recovery percentage were found to be in the range from 96.555 to 102.160. Normal ratio spectrophotometric method 0DD was used 50 mg/l acidic product as a divisor and then measured at 299.9 nm with correlat

    Simple, economic and sensitive mathematical spectrophotometric methods were developed for the estimation 4-aminoantipyrine in presence of its acidic product. The estimation of binary mixture 4-aminoantipyrine and its acidic product was achieved by first derivative and second derivative spectrophotometric methods by applying zero-crossing at (valley 255.9nm and 234.5nm) for 4-aminoantipyrine and (peak 243.3 nm and 227.3nm) for acidic product. The value of  coefficient of determination  for the liner  graphs were  not less than 0.996 and the recovery percentage were found to be in the range from 96.555 to 102.160. Normal ratio spectrophotometric method 0DD was used 50 mg/l acidic product as a divisor

Data hiding (Steganography) is a method used for data security purpose and to protect the data during its transmission. Steganography is used to hide the communication between two parties by embedding a secret message inside another cover (audio, text, image or video). In this paper a new text Steganography method is proposed that based on a parser and the ASCII of non-printed characters to hide the secret information in the English cover text after coding the secret message and compression it using modified Run Length Encoding method (RLE). The proposed method achieved a high capacity ratio for Steganography (five times more than the cover text length) when compared with other methods, and provides a 1.0 transparency by depending on som

Statistical methods and statistical decisions making were used to arrange and analyze the primary data to get norms which are used with Geographic Information Systems (GIS) and spatial analysis programs to identify the animals production and poultry units in strategic nutrition channels, also the priorities of food insecurity through the local production and import when there is no capacity for production. The poultry production is one of the most important commodities that satisfy human body protein requirements, also the most important criteria to measure the development and prosperity of nations. The poultry fields of Babylon Governorate are located in Abi Ghareg and Al_Kifil centers according to many criteria or factors such as the popu

In this paper, we will focus to one of the recent applications of PU-algebras in the coding theory, namely the construction of codes by soft sets PU-valued functions. First, we shall introduce the notion of soft sets PU-valued functions on PU-algebra and investigate some of its related properties.Moreover, the codes generated by a soft sets PU-valued function are constructed and several examples are given. Furthermore, example with graphs of binary block code constructed from a soft sets PU-valued function is constructed.

Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to