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

Drug overdose and poisoning are common clinical problems and could occur with Diphenhydramine hydrochloride (DFH) (one of anti histaminic drug ). It therefore important to study the adsorption of the DFH on pharmaceutical adsorbents which could serve as possible antidotes for the emergency treatment of DFH overdose or poisoning when they occur. The rate and extent of adsorption of DFH on some pharmaceutical adsorbents, bauxite were investigated spectra photometrically also the effect temperature, pH, presence of sucrose as additive have been studied as well, adsorbent's weight and partical size.The equilibrium adsorption contact times were determined for clay surface. Adsorption isotherms have been analyzed by the freundlich model. The appa

This article dealt with identifying the importance of heat stress in poultry flocks and the damages resulting from the production of eggs and meat and the spread of pathogens, in addition to that ways to mitigate the harmful effects of heat stress, including physiological, nutritional, engineering and genetics, in order to ensure preservation of the product and reduce damages

Breast 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