Deep learning of multi-layer computational models allowed processing to recognize data representation at multiple levels of abstraction. These techniques have greatly improved the latest ear recognition technology. PNN is a type of radiative basis for classification problems and is based on the Bayes decision-making base, which reduces the expected error of classification. In this paper, strong features of images are used to give a good result, therefore, SIFT method using these features after adding improvements and developments. This method was one of the powerful algorithms in matching that needed to find energy pixels. This method gives stronger feature on features and gives a large number of a strong pixel, which is considered a center and neglected the remainder of it in our work.
Each pixel of which is constant for image translation, scaling, rotation, and embedded lighting changes in lighting or 3D projection. Therefore, the interpretation is developed by using a hierarchical cluster method; to assign a set of properties (find the approximation between pixels) were classified into one.

As a result of the tremendous development in the field of information technology and the internet and exposure to a flood of violations to circumvent and steal information organized and unorganized. The urgent need for the emergence of data protection technologies and data encryption techniques. As a result of the tremendous development in the field of information technology and the internet and exposure to a flood of violations to circumvent and steal information organized and unorganized. The urgent need for the emergence of data protection technologies and data encryption techniques one of these methods, The Salsa20 encryption stream and all of its reduced versions Salsa20 / 7 and Salsa20 / 12 are among the fastest stream ciphers today. In this paper, the Salsa20 method is therefore improved by adding a new variable by using chaos theory which can achieve faster propagation than the original Salsa20 and has been applied by encrypting medical images that need confidentiality because some patients do not want anyone to know about a disease so the patient’s medical data is encrypted and no one can access it. This method has been tested and measured with the original Salsa20 with a series of tests. Most tests show that the proposed messy salsa is faster than the original salsa

Face recognition is method of recognizing individuals by facial expressions. It has become essential for security and surveillance applications, including banks, organisations, workplaces, and social areas, and is needed everywhere. In face recognition, there are a variety of difficulties faced, including face shape, age, sex, lighting, and other variable factors. Another problem is that the scale of the servers for these apps is relatively limited. Education and acknowledgment, thus, are increasingly complicated. In recent years, many unchanged features have been proposed in the literature, in this paper approach the use of the fast algorithm as local descriptors, and as we shall see, it is not only fixed-size features, but also offers the advantage of being highly efficient. The proposed approach allows distinguishing the destination after converting the image to the HSV system, after which the force field features will be extracted using the fast algorithm and then classification by using the distance for three methods (Manhattan, Euclidean, and Cosine) through which a comparison is made to choose the best resolution, as it was found that the resulting accuracy of the two dataset (ORL and UFI) is 99.9%.

The security aspect of processes and methodologies in the information and communication technology era is the main part. The security of information should a key priority in the secret exchange of information between two parties. In order to ensure the security of information, there are some strategies that are used, and they include steganography, watermark, and cryptography. In cryptography, the secrete message is converted into unintelligible text, but the existence of the secrete message is noticed, on the other hand, watermarking and steganography involve hiding the secrete message in a way that its presence cannot be noticed. Presently, the design and development of an effective image steganography system are facing several challenges such as the low capacity, poor robustness and imperceptibility. To surmount these challenges, a new secure image steganography work called the Pixels Variance (PV) method is proposed along with the eight neighbors method and Huffman coding algorithm to overcome the imperceptibility and capacity issues. In proposed method, a new image partitioning with Henon map is used to increase the security part and has three main stages (preprocessing, embedding, and extracting) each stage has different process. In this method, different standard images were used such as medical images and SIPI-dataset. The experimental result was evaluated with different measurement parameters such as Peak signal-to-noise ratio (PSNR) and Structural Similarity Index (SSIM). In short, the proposed steganography method outperformed the commercially available data hiding schemes, thereby resolved the existing issues.

Background: Melatonin, a neurohormone produced by the pineal gland, has recently been reported in foods, mainly of plant origin. Melatonin provides a number of benefits for human health. It has many important health benefits because it is a potent antioxidant and anti-inflammatory hormone. Objectives: The aim of this work is to investigate the relationship between malnutrition and food deprivation on melatonin levels in normal individuals in comparison with people suffering from gastrointestinal diseases. This study will focus on the nutritional factors apart from the intake of tryptophan that affects melatonin levels in humans. Materials and Methods: This study reported interests regarding the optimization, validation, and application of analytical liquid extraction and high-performance liquid chromatography (SYKAM) coupled to a fluorescence detector for the determination of melatonin in rice grains and blood samples. Results: In the present study, the results showed that there were significant differences between the three study groups, where the lowest values for melatonin hormone concentration were found in Group C as 2.033 ± 0.69 pg/mL which includes people suffering from famine, whereas the results of Group B showed clear differences of concentration than that in Group (C) as 3.520 ± 0.62 pg/mL which includes patients who were in hospital suffering from diseases and disorders of the digestive system, but at the same time their values were less than that of the healthy control Group A as 6.457 ± 0.59 pg/mL. Conclusion: Based on the present study, it can be concluded that melatonin hormone levels are highly deficient in people who are suffering from poverty, deprivation, and starvation compared to people with problems and disorders of the digestive system.