<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 curve (AUC), accuracy, receiver operating characteristic (ROC) curve, f-measure, and recall. Experimental results show that random forest is better than any other classifier in predicting diabetes with a 90.75% accuracy rate.</span>
The importance of the present work falls on the pitting corrosion behavior investigation of 304 SS and 316 SS alloys in 3.5 wt% of aqueous solution bearing with chloride and bromide anion at different solutions temperature range starting from (20-50)oC due to the pitting corrosion tremendous effect on the economic, safety and materials loss due to leakage. The impact of solution temperatures on the pitting corrosion resistance at 3.5wt% (NaCl and NaBr) solutions for the 304 SS and 316 SS has been investigated utilizing the cyclic polarization techniques at the potential range -400 to1000 mV vs. SCE at 40 mV/sec scan rate followed by the surface characterization employing Scanning Electron&nbs
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show Moreجريت التجربة في اصص فخارية سعة كل اصيص 4 كغم تربة في البيت الزجاجي التابع لقسم علوم الحياة/كلية التربية ابن الهيثـــــــــم/جـامعــة بـغداد لموســم النمـو 2008-2009 لدراســة تأثيــر اربعـــة مستويـــــات من سمــــاد اليوريـــا وهي (0, 0.1, 0.2, 0.4) غم/اصيص والتي تعادل (0, 100, 200, 400) كغم/هكتار وثلاث مستويات من سماد السوبر فوسفات وهي (0, 0.1, 0.2) غم/اصيص والتي تعادل (0, 100, 200) كغم/هكتارفي مكونـات الحاصـــل لنبــات الحلبـــة Trigonella foe
... Show MoreBackground: Elastomeric chains are one of the most commonly used force delivery systems. They have the ability to exert a continuous force, convenience of use, compatibility to oral environment and cost effectiveness but one of the inherited disadvantages is force degradation. Materials and methods: This in vitro study was designed to evaluate the effect of alcohol presence in mouthwashes on force decay of different configurations of clear elastomeric chains from (Ortho Technology company) which are: closed , short and long under the effect of time at (Initial, 1, 2, 3 and 4 weeks) intervals with exposure to different chemical solutions. A total (540) modules of elastomeric chains of three different types (long, short and closed) trans
... Show MoreStumpff functions are an infinite series that depends on the value of z. This value results from multiplying the reciprocal semi-major axis with a universal anomaly. The purpose from those functions is to calculate the variation of the universal parameter (variable) using Kepler's equation for different orbits. In this paper, each range for the reciprocal of the semi-major axis, universal anomaly, and z is calculated in order to study the behavior of Stumpff functions C(z) and S(z). The results showed that when z grew, Stumpff functions for hyperbola, parabola, and elliptical orbits were also growing. They intersected and had a tendency towards zero for both hyperbola and parabola orbits, but for elliptical orbits, Stumpff functions
... Show MoreIn this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th
... Show MoreIn this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes
Background: Bone mineral density (BMD) has been assessed using Dual-Energy X-ray absorptiometry (DEXA). This procedure is considered to be of vital importance in assessing the general condition of individuals concerning their skeletal mineralization. BMD is measured according to the results of the DEXA examination of the vertebral column and pelvis. Although diabetes mellitus (D.M.)is known to affect BMD, the information regarding this relationship is not currently particularly clear. Objective: This study concentrates on the point that the assessment of BMD for the vertebral column is insuffi-cient to give a realistic and correct picture of the mineralization of the remaining part of the skeleton. Besides, this study elicited a gen
... Show MoreThis research is devoted to investigate relationship between both Ultrasonic Pulse Velocity and Rebound Number (Hammer Test) with cube compressive strength and also to study the effect of steel reinforcement on these relationships.
A study was carried out on 32 scale model reinforced concrete elements. Non destructive testing campaign (mainly ultrasonic and rebound hammer tests) made on the same elements. About 72 concrete cubes (15 X 15 X15) were taken from the concrete mixes to check the compressive strength.. Data analyzed.Include the possible correlations between non destructive testing (NDT) and compressive strength (DT) Statistical approach is used for this purpose. A new relationships obtained from correlations results is give