In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.

Spatial and frequency domain techniques have been adopted in this search. mean
value filter, median filter, gaussian filter. And adaptive technique consists of
duplicated two filters (median and gaussian) to enhance the noisy image. Different
block size of the filter as well as the sholding value have been tried to perform the
enhancement process.

     The widespread use of images, especially color images and rapid advancement of computer science, have led to an emphasis on securing these images and defending them against intruders. One of the most popular ways to protect images is to use encryption algorithms that convert data in a way that is not recognized by someone other than the intended user. The Advanced Encryption Standard algorithm (AES) is one of the most protected encryption algorithms. However, due to various types of theoretical and practical assaults, like a statistical attack, differential analysis, and brute force attack, its security is under attack.

In this paper, a modified AES coined as (M-AES) is proposed to improve the efficiency

We will also derive practical solutions using predictive analytics. And this would include application making predictions with real world example from University of Faculty of Chariaa of Fez. As soon as student enrolled to the university, they will certainly encounter many difficulties and problems which discourage their motivation towards their courses and which pushes them to leave their university.
The aim of our article is to manage an investigation of the issue of dropping out their studies. This investigation actively integrates the benefits ofmachine learning. Hence, we will concentrate on two fundamental strategies which are KNN, which depends on the idea of likeness among data; and the famous strategy SVM, which can break the

     This work, aims to study and examine the description f the gradient reduced order-strategic sensors of type boundary exponential (-strategic sensors) for completion gradient  order-detectability of type boundary exponential (-detectability). Thus, this concept is linked to an estimator in distributed parameter systems (DPS_S) in Neumann problem. So,we present numerous consequences regarding to diverse kinds of information, region  and conditions of boundary region to allow existence of -detectable systems. In addition,we have estimated at the junction interface that the interior solution isharmonizedwith the exterior solution for -detectable and, we give the relationship between this concept and sensors structures. F

User confidentiality protection is concerning a topic in control and monitoring spaces. In image, user's faces security in concerning with compound information, abused situations, participation on global transmission media and real-world experiences are extremely significant. For minifying the counting needs for vast size of image info and for minifying the size of time needful for the image to be address computationally. consequently, partial encryption user-face is picked. This study focuses on a large technique that is designed to encrypt the user's face slightly. Primarily, dlib is utilizing for user-face detection. Susan is one of the top edge detectors with valuable localization characteristics marked edges, is used to extract

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

      The detection and estimation of weathering conditions have become a very important daily necessity in our life. For this purpose, several satellites of low resolution imagery were launched by the weathering and environmental agencies. The important weather paremeters are temperuter, wind direction,  velocity, clould and humidity, etc. The low resolution images often deal with large-scale phenomena and the interpretation and projection of the produced data requires continuous development of tools and criteria.              In this paper, the low spatial resolution data generated by the moderate resolution imaging spectroradiometer (MODIS) were used to monitor the cloud density and direction above Iraq and i