Background: Chronic otitis media (COM) of mucosal or squamous type is a common problem in otolaryngology practice, the active form of COM is characterized by discharge of pus and is treated by antibiotics to start with, the appropriate antibiotic should be prescribed to avoid antibiotic abuse and guarantee good outcome. Objectives:The objective of this study is to identify the causative organisms of active chronic active otitis media both (mucosal, squamous) type and test their sensitivity to various anti- microbial agents &compare with abroad studies.Methods:A prospective study was done on eighty patients, different ages and sexes were taken and carful history and examination was done, examination under microscope was done with carful suction to ensure absence of cholesteatoma, ear swabs were collected from middle ear discharge, bacteria identified by gram-staining and biochemical tests and antibiotic sensitivity were tested by using disc-perfusion method.Results:The culture results of eighty patients with chronic active otitis media, showed Pseudomonas aeroginosa from 26 patients (32.5%) and Proteus species from 18 patients (22.5%) and Staphylococcus aureus from 12 patients (15%), Providentia from 8 patients (10%) and Sarretia from 6 patients. (7.5%), mixed gram–ve bacteria isolated from 7.5% of patients, Klebsiella Ozaenae from 5%. of patients. no anaerobic bacteria were isolated in this study (table 1, 2).Antibiotic susceptibility showed sensitivity of Ps. Aeroginosa to menepem, third generation cephalosporin, ciprofluxacillin and resistance to gentamicin. Klebsiella Ozaenae showed resistant to many antibiotic also Serratia as shown in table 3. Conclusions:the microbial study of middle ear discharge is very important because the medical treatment is still a main part in treatment of chronic active otitis media so identifying the type of microorganisms and its sensitivity to antibiotics is give a good chance to successful control of the infection
This research includes the application of non-parametric methods in estimating the conditional survival function represented in a method (Turnbull) and (Generalization Turnbull's) using data for Interval censored of breast cancer and two types of treatment, Chemotherapy and radiation therapy and age is continuous variable, The algorithm of estimators was applied through using (MATLAB) and then the use average Mean Square Error (MSE) as amusement to the estimates and the results showed (generalization of Turnbull's) In estimating the conditional survival function and for both treatments ,The estimated survival of the patients does not show very large differences
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A theoretical study including the effects of the fusion characteristics parameters on the fundamental fusion rate for the BEC state in D-D fusion reaction is deal with varieties physical parameters such as the fuels density, fuel temperature and the astrophysics S-factor are processed to bring an approximately a comparable results to agree with the others previously studies.
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This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.
Experimental results shows LPG-
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Average interstellar extinction curves for Galaxy and Large Magellanic Cloud (LMC) over the range of wavelengths (1100 A0 – 3200 A0) were obtained from observations via IUE satellite. The two extinctions of our galaxy and LMC are normalized to Av=0 and E (B-V)=1, to meat standard criteria. It is found that the differences between the two extinction curves appeared obviously at the middle and far ultraviolet regions due to the presence of different populations of small grains, which have very little contribution at longer wavelengths. Using new IUE-Reduction techniques lead to more accurate result.
This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method
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