Introduction: The association between acute stroke and
renal function is well known. The aim of this study is to
know which group of patients with acute stroke is more
likely to have undiagnosed Chronic Kidney Disease and
which risk factors are more likely to be associated with.
Methods:We studied 77 patients who were diagnosed to
have an acute stroke.Patients were selected between
April2011andJune 2011 using the " 4-variable
Modification of
Diet in Renal Disease Formula " which estimates
Glomerular Filtration Rate using four variables :serum
creatinine ,age ,race and gender.
Results :The study included 38 male and 39 females
patients ,aged (35-95) years. Glomerular Filtration Rate in
patients wi
Diabetic nephropathy (DN) is a principle cause of microangiopathy and the main reason for kidney disease at the end stage in patients with type 2 diabetes mellitus (T2DM). This work aimed to study the relation of pentosidine with kidney injury in the case of diabetic nephropathy. This study included 75 patients suffering from T2DM and 75 apparently healthy subjects. The patients group was divided into three groups ((normoalbumin, microalbuminuria, and macroalbuminuria; 25 patients for each) on the basis of albumin-creatinine ratio (ACR) . The level of serum pentosidine was determined using an ELISA kit. The level of pentosidine was found to be significantly higher in DN patients than in the healthy group. Also, the results revealed a str
... Show MoreShadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.
Steganography is a useful technique that helps in securing data in communication using different data carriers like audio, video, image and text. The most popular type of steganography is image steganography. It mostly uses least significant bit (LSB) technique to hide the data but the probability of detecting the hidden data using this technique is high. RGB is a color model which uses LSB to hide the data in three color channels, where each pixel is represented by three bytes to indicate the intensity of red, green and blue in that pixel. In this paper, steganography based RGB image is proposed which depends on genetic algorithm (GA). GA is used to generate random key that represents the best ordering of secret (image/text) blocks to b
... Show MoreWater/oil emulsion is considered as the most refractory mixture to separate because of the interference of the two immiscible liquids, water and oil. This research presents a study of dewatering of water / kerosene emulsion using hydrocyclone. The effects of factors such as: feed flow rate (3, 5, 7, 9, and 11 L/min), inlet water concentration of the emulsion (5%, 7.5%, 10%, 12.5%, and 15% by volume), and split ratio (0.1, 0.3, 0.5, 0.7, and 0.9) on the separation efficiency and pressure drop were studied. Dimensional analysis using Pi theorem was applied for the first time to model the hydrocyclone based on the experimental data. It was shown that the maximum separation efficiency; at split ratio 0.1, was 94.3% at 10% co
... Show MoreCompressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp
... Show MoreEye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz & Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through genera
... Show MoreNeural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.
Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
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