Cyber security is a term utilized for describing a collection of technologies, procedures, and practices that try protecting an online environment of a user or an organization. For medical images among most important and delicate data kinds in computer systems, the medical reasons require that all patient data, including images, be encrypted before being transferred over computer networks by healthcare companies. This paper presents a new direction of the encryption method research by encrypting the image based on the domain of the feature extracted to generate a key for the encryption process. The encryption process is started by applying edges detection. After dividing the bits of the edge image into (3×3) windows, the diffusions on bits are applied to create a key used for encrypting the edge image. Four randomness tests are passed through NIST randomness tests to ensure whether the generated key is accepted as true. This process is reversible in the state of decryption to retrieve the original image. The encryption image that will be gained can be used in any cyber security field such as healthcare organization. The comparative experiments prove that the proposed algorithm improves the encryption efficiency has a good security performance, and the encryption algorithm has a higher information entropy 7.42 as well as a lower correlation coefficient 0.653.
Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area. The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and
... Show MoreThis work deals with the preparation of a zeolite/polymer flat sheet membrane with hierarchical porosity and ion-exchange properties. The performance of the prepared membrane was examined by the removal of chromium ions from simulated wastewater. A NaY zeolite (crystal size of 745.8 nm) was prepared by conventional hydrothermal treatment and fabricated with polyethersulfone (15% PES) in dimethylformamide (DMF) to obtain an ion-exchange ultrafiltration membrane. The permeate flux was enhanced by increasing the zeolite content within the membrane texture indicating increasing the hydrophilicity of the prepared membranes and constructing a hierarchically porous system. A membrane contain
In this study, light elements 19F ,22Na for (α,n) and (n,α) reactions as well as α-particle energy from a threshold energy to 10 MeV are used according to the available data of reaction cross sections. The more recent cross sections data of (α,n) and (n,α) reactions are reproduced in fine steps 86.4 KeV for 22Na (n,α) 19F in the specified energy range, as well as cross section (α,n) values were derived from the published data of (n,α) as a function of αenergy in the same fine energy steps by using the principle inverse reactions. This calculation involves only the ground state of 19F ,22Na in the reactions 19F (α,n) 22Na , 2
... Show MoreThe study aimed at designing a training program by using training for the anaerobic differential threshold stand and the effects of those trainings on the variables of (Concentration of Lactic Acid and LDH Enzyme, VO2 MaX and Cortisol Hormone). The Researchers used the experimental program with one-group style. Also, they used a sample with (8) men-players in a (free 400 m men-runners) and they used many instruments and procedures, most notably the training-program prepared for 10 weeks and for 3 training units weekly, (70-90 min) for each unit. They used the training intensity from 85-100% of the player's ability. After finishing the training program and doing some pre-tests and post-tests then statistically checking the results, the resea
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