Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor

For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers

Intrusion-detection systems (IDSs) aim at detecting attacks against computer systems and networks or, in general, against information systems. Most of the diseases in human body are discovered through Deoxyribonucleic Acid (DNA) investigations. In this paper, the DNA sequence is utilized for intrusion detection by proposing an approach to detect attacks in network. The proposed approach is a misuse intrusion detection that consists of three stages. First, a DNA sequence for a network traffic taken from Knowledge Discovery and Data mining (KDD Cup 99) is generated. Then, Teiresias algorithm, which is used to detect sequences in human DNA and assist researchers in decoding the human genome, is used to discover the Shortest Tandem Repeat (S

Most includeding techniques of digital watermark even now working through the direct inclusion in the pixel without taking into account the level of compression (attack) that can go wrong, which makes digital watermark can be discarded easily. In this research, a method was proposed to overcome this problem, which is based on DCT (after image partitioned into non overlapped blocks with size 8×8 pixel), accompanied by a quantization method. The watermark (digital image) is embedded in DCT frequency domain seeking the blocks have highest standard deviation (the checking is only on the AC coefficients) within a predetermined threshold value, then the covered image will compressed (attacked) varying degrees of compression. The suggested met

Background: image processing of medical images is major method to increase reliability of cancer diagnosis.
Methods: The proposed system proceeded into two stages: First, enhancement stage which was performed using of median filter to reduce the noise and artifacts that present in a CT image of a human lung with a cancer, Second: implementation of k-means clustering algorithm.
Results: the result image of k-means algorithm compared with the image resulted from implementation of fuzzy c-means (FCM) algorithm.
Conclusion: We found that the time required for k-means algorithm implementation is less than that of FCM algorithm.MATLAB package (version 7.3) was used in writing the programming code of our w