Video steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion. This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The XOR technique is used with reverse bits between the secret image bits and the detected moving object bits for embedding. The proposed method provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the

The aim of t his p aper is t o const ruct t he (k,r)-caps in t he p rojective 3-sp ace PG(3,p ) over Galois field GF(4). We found t hat t he maximum comp let e (k,2)-cap which is called an ovaloid, exist s in PG(3,4) when k = 13. Moreover t he maximum (k,3)-cap s, (k,4)-cap s and (k,5)-caps.

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

        The current research studies the innovative thinking system in the field of the interior design, and the extent of the possibility of activating its work mechanisms as a strategy for the redesigning principle according the variables of the contemporary social thinking. The research aims at revealing the nature of the thinking criteria and requirements that provide strategic values that guide the interior designer and the architect to organize the mechanism the act of designing. It also contributes in dealing with the design product through activating its ability in innovation and redesigning.

       The research consists of the concept of innovation, the&nbs

Radiation measuring devices need to periodic calibration process to examine their sensitivity and the extent of the response. This study is used to evaluate the radiation doses of the workers in the laboratories of the Directorate of Safety as a result of the use of point sources in calibrating of the devices in two ways, the first is the direct measurement by the FAG device and the others using RESRAD and RAD PRO programs. The total doses values using FAG were (2.57 μSv/y, 102.3 μSv/y and 20.75 μSv/y for TLD laboratory, Gamma spectroscopy analyses (GSA) laboratory and equipment store respectively, and the total doses that calculated using RESRAD and RAD PRO were 1.518 μSv/y, 76.65 μSv/y and 21.2 μSv/y for the above laboratories. t