<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>
Diabetes mellitus is a common health problem worldwide counting about 1.2 million cases in Iraq in 2015. Taking in account of the patient’s beliefs about the prescribed medication had been reported to be one of the most important factors that affects adherence where holding positive beliefs about medications is a prerequisite for intentional adherence. The aim of the current study was to investigate and assess beliefs about medicines among type 2 diabetic patients and to determine possible association between this belief and glycemic control as well as some patient-specific factors. This study is a cross-sectional study carried out on 380 (mean age 56.58± 10.06 years) already diagnosed T2DM patients who attended the National Diabetes
... Show MoreThis research focuses on studying the effects of soil movement on the behavior of an existing pile driven in sandy soil. A physical model has been manufactured to investigate the effect of construction of an embankment adjacent to free head single pile driven in sand of dry unit weight of 13.5 kN/m3. The model pile of diameter (D) of 10 mm are tested under two conditions of loading: loaded axially and without load. The model piles are instrumented with strain gauges along the embedded length to measure strains resulting from the soil movement. The embankment loads are applied at distances of 2.5, 5, and 10D from the edge of the pile. The results obtained from the
The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t
... Show MoreThe field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots. To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura
... Show MoreIn this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.
Assume that is a meromorphic fuction of degree n where X is compact Riemann surface of genus g. The meromorphic function gives a branched cover of the compact Riemann surface X. Classes of such covers are in one to one correspondence with conjugacy classes of r-tuples ( of permutations in the symmetric group , in which and s generate a transitive subgroup G of This work is a contribution to the classification of all primitive groups of degree 7, where X is of genus one.
Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio
... Show MoreThe research shows the importance of orientation towards the formulation of the green strategy and its effect in determining the behavior of the green municipal institution in Babel governorate. The research highlighted the formulation of the green strategy as an important variable, especially today, the trend towards protecting the environment and minimizing the damage resulting from the delivery of services, and through it also the type of green behavior or performance adopted by the municipal institution and the emergence of the need for a strategy that is not harmful to the environment. The research took the sample intentionally comprehensive size of 222 personnel of municipal institutions and some formations concerned with t
... Show MoreThe corrosion behavior of Titanium in a simulated saliva solution was improved by Nanotubular Oxide via electrochemical anodizing treatment using three electrodes cell potentiostat at 37°C. The anodization treatment was achieved in a non-aqueous electrolyte with the following composition: 200mL ethylene glycol containing 0.6g NH4F and 10 ml of deionized water and using different applied directed voltage at 10°C and constant time of anodizing (15 min.). The anodized titanium layer was examined using SEM, and AFM technique.
The results showed that increasing applied voltage resulted in formation titanium oxide nanotubes with higher corrosion resistance
Previous studies indicated that supplementation with antioxidants has a protective effects against oxidative stress–induced damage in type 2 diabetes. In this study we evaluated the antioxidant effects of melatonin on the oxidative stress parameters and microalbuminuria in type 2 DM patients. 30 patients with type 2 DM were treated with 3mg/day melatonin for 90 days. Erythrocytes and plasma MDA and glutathione, fasting plasma glucose, %HbAIC, microalbuminuria, total plasma protein and lipid profile were measured each 30 days and compared with those obtained from 20 healthy controls.
A decrease in MDA levels associated with the elevation in GSH levels were observed, compared with the pre–treatment levels.
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