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 Si

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

Leinamycin is a thiol dependent DNA alkylating agent which shows very potent activity against various cancer cell lines. This natural compound forms guanine adducts (N7) in DNA which are converted into a basic sites and simultaneously generates Reactive Oxygen Species (ROS), to produce DNA strand breaks in human cancer cells. In present study, eight different strains isolated from Iraqi soils were taxonomically assigned as Streptomyces.atroolivaceous. Remarkably the strain named as THS-44 was distinguished in productivity in comparison with other strains; the amount of leinamycin was 50.98 mg/l. In this study, we assessed the cytotoxic activity of leinamycin against RD and ANM3 cancer cell line in compare with REF cell line as a normal cont

     The research problem revolves around the failure of Maysan Oil Company to have a strategy that enables it to keep up with work in a mysterious and highly dynamic environment. Therefore, the research aims to present a proposed strategy that is comprehensive and realistic to the Maysan Oil Company for the next five years (2020-2024) based on the position and conditions of the company Current and future by adopting the scientific foundations for formulating the strategy, and the importance of research lies in the company's situational analysis to know its internal capabilities from strengths or weaknesses and diagnosing the surrounding elements of opportunities or threats so that this analysis represents a s

The purpose of this study is to measure the levels of quality control for some crude oil products in Iraqi refineries, and how they are close to the international standards, through the application of statistical methods in quality control of oil products in Iraqi refineries. Where the answers of the study sample were applied to a group of Iraqi refinery employees (Al-Dora refinery, Al-Nasiriyah refinery, and Al-Basra refinery) on the principles of quality management control, and according to the different personal characteristics (gender, age, academic qualification, number of years of experience, job level). In order to achieve the objectives of the study, a questionnaire that included (12) items, in order to collect preliminary inform

Filed experiment was conducted to test the effect of saline water and potassium fertilizers rate on proline and water potential of Pisum sativum L. (Var.Senador Cambados ) leaves . Treatments of the experiment included two levels of water salinity( 2, 7 dSm-1) as a main plot and fertilizer rates as a sub plot. Results indicated that irrigation of plant with saline water 7 dSm-1 and fertilization 150 kg/donum increased proline accumulation and water potential 0.31 mmol/g,-17.00 bar at 9 AM morning and 0.62 mmol/g , -21.00 bar at 3 PM afternoon ,Irrigating plant with a 2 dSm-1 and fertilization 300 kg/donum decreased proline accumulation and water potential of leaves 0.22 mmol/g, -16.00 bar at 9 A

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.