A new spectrophotometric method for the determination of allopurinol drug was investigated. The proposed method was based on the reaction of the intended drug with catechol and Fe(II) to form a blue soluble complex which was measured at λmax 580 nm. A graph of absorbance versus concentration shown that Beer’s law was obeyed over the concentration range of 2–10 μg ml–1 with molar absorptivity of 9.4 x 103 l mol–1 cm–1 and Sandell sensitivity of 1.4 x 10–2 μg cm–2. A recovery percentage of 100% with RSD of 1.0%–1.3% was obtained. The proposed method was applied successfully for the determination of allopurinol drug in tablets with a good accuracy and

The research study includes shedding light on the sas dance in Iraq, as it is one of the popular legacies that are rich in the Mesopotamian civilization and because of the different practices it has in the different occasions on which these dances are held. Which is one of the kinetic arts widespread among the classes of Iraqi society. The researcher explained its features and artistic content that characterizes Iraqi music. The (methodological framework) reviewed the justification, importance and purpose of the research, and the limits of the research that included the (National Troupe of Folk Art) as a human limit to discover the artistic methods of the Sas dance and then define the terms of the search. The "theoretical framework" cont

We report a method of converting non-conductive plastic surfaces into conductive by plating either copper electroless or copper electroplating -carbon black containing bending Agent onto Perspex plastics . Various approaches have been studied in order to comparing properties of the plated copper for two methods such as scanning electron microscopy (SEM),thickness, roughness, porosity, tensile Strength and elongation. The results show that the surface of electroplating was uniform, compact, and continuous and it had an obvious metallic sheen, while the surface of plated copper for electroless for it had many pores. Also observed that the coating was composed of small cells. Thes

Construction projects are complicated in nature and require many considerations in contractor selection. One of the complicated interactions is that between performance with the project size, and contractor financial status, and size of projects contracted. At the prequalification stage, the financial ‎requirements restrict the ‎contractors to meet minimum limits in financial criteria such as net worth, working capital and ‎annual turnover, etc. In construction projects, however, there are cases when contractors meet these requirements but show low performance in practice. The model used in the study predicts the performance by training of a neural network. The data used in the study are 72 of the most recent roadw

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.

The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC

This research investigates the methods of producing Investigative Arabic Television Programs that are able to prove its existence during a short period of time as a form of Television programs on Arab satellite channels growing in number and varied in content. The research aims to present qualitative and quantitative descriptions of the methods used in tackling the topics discussed in the program, and knowing whether they satisfy the conditions and scientific foundations for the research, investigation, analysis, and interpretation. The researcher uses the survey method and uses the tool of content analysis including a set of methodological steps that seek to discover the implied meaning of the research sample represented by the program

The acceptance sampling plans for generalized exponential distribution, when life time experiment is truncated at a pre-determined time are provided in this article. The two parameters (α, λ), (Scale parameters and Shape parameters) are estimated by LSE, WLSE and the Best Estimator’s for various samples sizes are used to find the ratio of true mean time to a pre-determined, and are used to find the smallest possible sample size required to ensure the producer’s risks, with a pre-fixed probability (1 - P^*). The result of estimations and of sampling plans is provided in tables.

Key words: Generalized Exponential Distribution, Acceptance Sampling Plan, and Consumer’s and Producer Risks

Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a