High-performance liquid chromatographic methods are used for the determination of water-soluble vitamins with UV-Vis. Detector. A reversed-phase high-performance liquid chromatographic has been developed for determination of water-soluble vitamins. Identification of compounds was achieved by comparing their retention times and UV spectra with those of standards solution. Separation was performed on a C18 column, using an isocratic 30% (v/v) acetonitril in dionozed water as mobile phase at pH 3.5 and flow rate 1.0m/min. The method provides low detection and quantification limits, good linearity in a large concentration interval and good precision. The detection limits ranged from 0.01 to 0.025µg/ml. The accuracy of the method was

Background: The bonded orthodontic retainer constructed from multistrand wire and composite is an efficient esthetic retainer, which can be maintained long-term. Clinical failures of bonded orthodontic retainers, most commonly at the wire/composite interface, have been reported. This in vitro investigation aimed to evaluate the tensile forces of selected multistrand wires and composite materials that are available for use in the construction of bonded fixed retainers. Materials and Methods: The study sample includes 120 wires with three types of retainer wires (3 braided strands\ Orthotechnology, 8 braided strands\ G&H Orthodontics, 6 coaxial strands\ Orthoclassic wires), two types of adhesive (flowable\ Orthotechnology, non flowable\ G&H O

Election study included four sites for the waters in area of Youssifiyah south of Baghdad (river water, tank water, liquefactions water, and water filtrate and seethed and purifier by alum and chloride), the samples were collected during the month of June in 2007. Temperature, electrical conductivity and acidity are measured. Also , the concentration of chloride , sulphate , carbonate , nitrate , sodium , calcium , magnesium , hard total and total dissolved substances are determined , as well as heavy metals assess environmental risk (such as Cu, Pb, Zn, Fe). It was also a study of bacterial totals included both total Bacteria (TB) and Total Coliform Bacteria (TC) and Fecal Coliform (FC) and Fecal Streptococci (FS). The stu

Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

Knowledge of the mineralogical composition of a petroleum reservoir's formation is crucial for the petrophysical evaluation of the reservoir. The Mishrif formation, which is prevalent in the Middle East, is renowned for its mineralogical complexity. Multi-mineral inversion, which combines multiple logs and inversions for multiple minerals at once, can make it easier to figure out what minerals are in the Mishrif Formation. This method could help identify minerals better and give more information about the minerals that make up the formation. In this study, an error model is used to find a link between the measurements of the tools and the petrophysical parameters. An error minimization procedure is subsequently applied to determine