An approach for hiding information has been proposed for securing information using Slanlet transform and the T-codes. Same as the wavelet transform the Slantlet transform is better in compression signal and good time localization signal compression than the conventional transforms like (DCT) discrete cosine transforms. The proposed method provides efficient security, because the original secret image is encrypted before embedding in order to build a robust system that is no attacker can defeat it. Some of the well known fidelity measures like (PSNR and AR) were used to measure the quality of the Steganography image and the image after extracted. The results show that the stego-image is closed related to the cover image, with (PSNR) Peak Signal to Noise Ratio is about 55dB. The recovered secret image is extracted (100%) if stego-image has no attack. These methods can provide good hiding capacity and image quality. Several types of attacks have been applied to the proposed methods in order to measure the robustness like (compression, add noise and cropping). The proposed algorithm has been implemented by using computer simulation program MATLAB version 7.9 under windows 7 operating system by Microsoft cooperation.
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MS Elias, RGM AL-helfy, Plant Archives, 2019
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Was conducted neutralize content Albulamedi for local isolates using Alacardan dye orange selection experience showed loss of local isolates resistant life antibiotic ampicillin, chloramphenicol
Of the new concepts introduced by the decree of the amendment of the French Civil Code No. 131-2016 issued on 10 February 2016, which raised a debate in jurisprudence both at the level of French jurisprudence or the Arab, the concept of (the content of the contract), which seems to have emerged from the appearance of new legal articles ( 1162-1171) is the cornerstone of the contract and the contract in the contract, the two pillars which, over the course of 200 years and a half, have been one of the main pillars of the codification of Napoleon. Is that the decree of amendment has already abandoned these two pillars, or most of what he did is a change in terminology while preserving the content of these two pillars implicitly, this is what w
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Background: Large amounts of oily wastewater and its derivatives are discharged annually from several industries to the environment. Objective: The present study aims to investigate the ability to remove oil content and turbidity from real oily wastewater discharged from the wet oil's unit (West Qurna 1-Crude Oil Location/ Basra-Iraq) by using an innovated electrocoagulation reactor containing concentric aluminum tubes in a monopolar mode. Methods: The influences of the operational variables (current density (1.77-7.07 mA/cm2) and electrolysis time (10-40 min)) were studied using response surface methodology (RSM) and Minitab-17 statistical program. The agitation speed was taken as 200 rpm. Energy and electrodes consumption had been studi
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The objective of this study is to attempt to provide a quantitative analysis to the causes of unemployment in Iraq and its mechanisms of generation, as well as a review of the most important types of both visible and invisible unemployment, and an attempt to measure the disguised unemployment and analyze the causes. The problem of the research lies in the fact that the Iraqi Economy has been suffered for a long time although its characterized by abundant physical and natural resources, from the existence of the phenomenon of unemployment in the previous two types. Causing a lot of economic problems, represented by the great waste of resources and
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
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