A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

This study was conducted to determine the fungal cause and bio control of damping off and root rot of wheat plants by using pseudomonas fluorescens under greenhouse and field conditions. Results showed isolation of eight species from the soil and roots to deferent region of Baghdad government. Rhizoctonia solani (Rs) and Fusarium solani (Fs) were the predominant damping off fungus with frequency 60 and 52% respectively. Led the using of bacteria formulations such as crud suspension , pure bacteria filtration and pure living cells in culture medium inhibit all type fungi with rates ranging from 84-96% , 80- 93% and 75-88% respectively. Rs and Fs were more pathogenesis under greenhouse conditions, with incidence of 80 and 68% and disease s

The aim of the research is to identify an appropriate training method that raises the levels of immune globulins (IgA, IgM, IgG) and white blood cells and the effect of training by (HIT) method using resistance (weights) as a training curriculum that increases immunity and ensures the continuation of the pills after the return of activity from the stone The response to the Covid-19 epidemic among amateur weightlifters, the researchers relied on the method of trace analysis in an experimental way by conducting a pre-, medial and post-test with the same experimental one agroup on a sample of amateur weightlifters in the Fury private hall for weightlifting and body building in Adhamiya, the number of sample members reached (15 players) who int

Background: L. sativum, are traditionally used for the treatment of various diseases and thought to have medicinal value. Isolates from many part of the world is now multidrug resistant. Therefore, there is an urgent need to look for and test an alternative herbal drug.

Objective: The present study aimed to evaluate the antibacterial activity of L. Sativum seed extract against multi drug resistant (MDR) and sensitive Pseudomonas aeruginosa clinical isolates.

Subjects and Methods: An ethanolic and aqueous stock extracts were prepared from L.  sativum seed plant then serial dilutions were prepared and the obtained concentrations (50, 25, 12.5 and 6.2 mg/ml) were tested against 30 multidrug-resistan

This paper deals with the modeling of a preventive maintenance strategy applied to a single-unit system subject to random failures.

According to this policy, the system is subjected to imperfect periodic preventive maintenance restoring it to ‘as good as new’ with probability

p and leaving it at state ‘as bad as old’ with probability q. Imperfect repairs are performed following failures occurring between consecutive

preventive maintenance actions, i.e the times between failures follow a decreasing quasi-renewal process with parameter a. Considering the

average durations of the preventive and corrective maintenance actions a

Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co

          This study was done to evaluate a new technique to determine the presence of methamphetamine in the hair using nano bentonite-based adsorbent as the filler of extraction column. The state of the art of this study was based on the presence of silica in the nano bentonite that was assumed can interact with methamphetamine. The hair used was treated using methanol to extract the presence of methamphetamine, then it was continued by sonicating the hair sample. Qualitative analysis using Marquish reagent was performed to confirm the presence of methamphetamine in the isolate.The hair sample that has been taken in a different period confirmed that this current developing method can be used to analyzed methamphetamine. This m

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne