The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca

Background: Infection with Hepatitis C virus (HCV) is a major cause of chronic liver disease, WHO estimated that about 170 million people are infected with Hepatitic C virus, Silymarin (Legalon) have been recently shown to be effective in treatment of Hepatitic C virus infection.
Objectives: The effectiveness of Legalon (Silymarin) on viral load in patients with Hepatitic C virus infection.
Patients and methods: A prospective case – control study included 400 patients with Hepatitis C virus infection. 200 patients (group A) were treated with (peg-interferon, ribavirin, silymarin) the other 200 patients (group B) were treated with (peg-interferon, ribavirin) . only G1 & G4 genotypes were included , viral load were assessed ini

    The search included a comparison between two etchands for etch CR-39 nuclear track detector, by the calculation of bulk etch rate (Vb) which is one of the track etching parameters, by two measuring methods (thichness and change mass). The first type, is the solution prepared  from solving NaOH in Ethanol (NaOH/Ethanol) by varied normalities  under temperature(55ËšC)and etching time (30 min) then comparated with the second type the solution prepared from solving NaOH in water (NaOH/Water) by varied normalities with (70ËšC) and etching time (60 min) . All detectors were irradiated with (5.48 Mev) α-Particles from an 241Am source in during (10 min). The results that Vb would increase with the increase of

ABSTRACT Background: chronic periodontitis and rheumatoid arthritis are widely prevalent diseases and are characterized by tissue destruction due to chronic inflammation. Recently, there is growing evidence that the two diseases share many pathological features the aims of the study To determine the periodontal health status in patient have chronic periodontitis with rheumatoid arthritis and compare it with those having chronic periodontitis without Rheumatoid arthritis and determine the serum levels of interleukin -17(IL-17), tumor necrosis factor- alpha (TNF-α ) in both groups and compare with the control group (subject samples neither have periodontitis nor arthritis ) and correlate these immunological markers with the periodontal p

Patient satisfaction and dental anxiety considered as an important factors in dental health care and treatment because they greatly affect the patient's cooperation with the dentist and the extent to which follows the guidelines, treatment and preventive instruction. The present study investigates the relationship between patient satisfaction and dental anxiety, as well as their relation to demographic variables such as gender, age, number of visits, and cultural level. The study was applied on a random sample of dental clinics in Baghdad city with total of (200) patient (108 male and 92 female). Two scales were used in this study, patient satisfaction scale PSS (included 9 aspects, constructed by authors) and Iraqi dental anxiety scale

In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

There is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

This research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).