Image recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third level. The two techniques that have the best results which are (sww and www) are chosen, then image recognition is applied to these two techniques using Euclidean distance and Manhattan distance and a comparison between them has been implemented., it is concluded that, sww technique is better than www technique in image recognition because it has a higher match performance (100%) for Euclidean distance and Manhattan distance than that in www..
Hypertension is a cardiovascular problem with high rates of epidemiology and risks of morbidity and mortality in the global area. Nitric oxide (NO) is one of the reactive oxygen species (ROS) that produced from L-arginine by nitric oxide synthase (NOS) enzyme. NO involves in various vital processes in human health, one of which is the modulation of vasoconstriction and relaxation of the vascular system. We have aimed to investigate the link between NO and NOS with hypertension in women. The relationship between NO and NOS, as well as the usefulness of them as indicators of hypertension risks were subjects of study in this article. The results have revealed that hypertensive women had significant (P<0.05) lower levels of NO (15.07±3.41 IU/m
... Show MoreRheumatoid arthritis (RA), is an autoimmune, and inflammatory disease that is closely related to the destruction of cartilage and bone. DC-SIGN are important types of C-type lectin receptors (CLRs), expressed on dendritic cells and macrophages, and have a central role in regulating innate and adaptive immunity, function as pattern recognition receptors, and as cell adhesion molecules. Recent evidence has demonstrated that DC-SIGN is involved in the pathophysiological of chronic inflammation, so DC-SIGN has been linked to several autoimmune and may play an essential indicator in the pathogenesis and progression of RA. Therefore, the purpose of this study is to determine the serum level of DC-SIGN in RA patients, as well as the level of DC
... Show MoreBackground: H.pylori colonized gastric mucosal
epithelium will virtually develop gastritis and had the
capacity to persist for decades. Pathogenesis is
dependent upon strain, virulence host genetic
susceptibility, and environmental cofactors. Leptin is
a member of the class 1 cytokine family so altered
leptin production during ifnect and inflammation that
leptin part of the cytokine cascade ,which
orchestrates the defense mechanism.
Objective: Examin the effect of H.pylori infection
on serum leptin level.
Methods: One hundred and thirty(130) Patients
attending the Endoscopic Unit at "Gastroenterology
and Hepatology Teaching Hospital/ Baghdad Medical
City"were included in this study with ages rang
Roughness length is one of the key variables in micrometeorological studies and environmental studies in regards to describing development of cities and urban environments. By utilizing the three dimensions ultrasonic anemometer installed at Mustansiriyah university, we determined the rate of the height of the rough elements (trees, buildings and bridges) to the surrounding area of the university for a radius of 1 km. After this, we calculated the zero-plane displacement length of eight sections and calculated the length of surface roughness. The results proved that the ranges of the variables above are ZH (9.2-13.8) m, Zd (4.3-8.1) m and Zo (0.24-0.48) m.
Researchers used different methods such as image processing and machine learning techniques in addition to medical instruments such as Placido disc, Keratoscopy, Pentacam;to help diagnosing variety of diseases that affect the eye. Our paper aims to detect one of these diseases that affect the cornea, which is Keratoconus. This is done by using image processing techniques and pattern classification methods. Pentacam is the device that is used to detect the cornea’s health; it provides four maps that can distinguish the changes on the surface of the cornea which can be used for Keratoconus detection. In this study, sixteen features were extracted from the four refractive maps along with five readings from the Pentacam software. The
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