This study aims to determine the prevalence of Entamoeba histolytica, Entamoeba dispar and
Entamoeba moshkovskii by three methods of diagnosis (microscopic examination, cultivation and PCR) that
were compared to obtain an accurate diagnosis of Entamoeba spp. during amoebiasis. Total (n=150) stool
samples related to patients were (n = 100) and healthy controls (n= 50). Clinically diagnosed stool samples
(n=100) were collected from patients attending the consultant clinics of different hospitals in Basrah during
the period from January 2018 to January 2019. The results showed that 60% of collected samples were
positive in a direct microscopic examination. All samples were cultivated on different media; the Brain heart
infusion agar showed high efficiency and was the most suitable in cultivating the parasite. Data and results of
molecular study were indicated by DNA extraction from stool samples and used in PCR technique with
specific primers. This study identifies different infection percentage for the three species. The highest
infection in Basrah patients was Entamoeba moshkovskii 15% followed by Entamoeba dispar 10% and
Entamoeba histolytica, which was 5%.
In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm.
In this paper, we introduce a DCT based steganographic method for gray scale images. The embedding approach is designed to reach efficient tradeoff among the three conflicting goals; maximizing the amount of hidden message, minimizing distortion between the cover image and stego-image,and maximizing the robustness of embedding. The main idea of the method is to create a safe embedding area in the middle and high frequency region of the DCT domain using a magnitude modulation technique. The magnitude modulation is applied using uniform quantization with magnitude Adder/Subtractor modules. The conducted test results indicated that the proposed method satisfy high capacity, high preservation of perceptual and statistical properties of the steg
... Show MoreIn this paper, we designed a new efficient stream cipher cryptosystem that depend on a chaotic map to encrypt (decrypt) different types of digital images. The designed encryption system passed all basic efficiency criteria (like Randomness, MSE, PSNR, Histogram Analysis, and Key Space) that were applied to the key extracted from the random generator as well as to the digital images after completing the encryption process.
As s widely use of exchanging private information in various communication applications, the issue to secure it became top urgent. In this research, a new approach to encrypt text message based on genetic algorithm operators has been proposed. The proposed approach follows a new algorithm of generating 8 bit chromosome to encrypt plain text after selecting randomly crossover point. The resulted child code is flipped by one bit using mutation operation. Two simulations are conducted to evaluate the performance of the proposed approach including execution time of encryption/decryption and throughput computations. Simulations results prove the robustness of the proposed approach to produce better performance for all evaluation metrics with res
... Show MoreBreast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we
... Show MoreThis study has applied digital image processing on three-dimensional C.T. images to detect and diagnose kidney diseases. Medical images of different cases of kidney diseases were compared with those of healthy cases. Four different kidneys disorders, such as stones, tumors (cancer), cysts, and renal fibrosis were considered in additional to healthy tissues. This method helps in differentiating between the healthy and diseased kidney tissues. It can detect tumors in its very early stages, before they grow large enough to be seen by the human eye. The method used for segmentation and texture analysis was the k-means with co-occurrence matrix. The k-means separates the healthy classes and the tumor classes, and the affected
... Show MoreThe research aims to monitor environmental changes and study the state of desertification in the northeastern part of the Al-Najaf province, Iraq. The study area suffers from desertification and drought phenomena. Remote sensing systems "RS" and geographic information systems "GIS" are essential for monitoring environmental changes because they provide Earth observation satellites that contribute to detecting environmental changes. Two Sentinel 2 images were acquired on December 26, 2015, and November 29, 2021. The images were combined and used for indices calculations. Normalized vegetation difference index "NDVI,” Normalized difference index "NDWI," soil exposure index "BSI," and Normalized difference index "NDBI." The resul
... Show MoreThe Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process