In the present work, classification of radioactive wastes based on Annual Intake (AI) values is studied. Where the characterization of radionuclides was done by hand held GeLi detector with an overall efficiency better than 42%. It was noted the most predominant contaminant are Cs-137, Co-60 and Pa-234.The radioactive waste in disposal silo has been divided into five categories according to the harmful effect of radionuclides.For the purpose of storageradioactive wastein a safe manner, it wassuggesteda new method by shielding radioactive waste in each category with concrete;where the thickness of shielding is the time required to reduce the annual dose to 10%.

Wellbore instability is one of the most common issues encountered during drilling operations. This problem becomes enormous when drilling deep wells that are passing through many different formations. The purpose of this study is to evaluate wellbore failure criteria by constructing a one-dimensional mechanical earth model (1D-MEM) that will help to predict a safe mud-weight window for deep wells. An integrated log measurement has been used to compute MEM components for nine formations along the studied well. Repeated formation pressure and laboratory core testing are used to validate the calculated results. The prediction of mud weight along the nine studied formations shows that for Ahmadi, Nahr Umr, Shuaiba, and Zubair formations

    The digital world has been witnessing a fast progress in technology, which led to an enormous increase in using digital devices, such as cell phones, laptops, and digital cameras. Thus, photographs and videos function as the primary sources of legal proof in courtrooms concerning any incident or crime. It has become important to prove the trustworthiness of digital multimedia. Inter-frame video forgery one of common types of video manipulation performed in temporal domain. It deals with inter-frame video forgery detection that involves frame deletion, insertion, duplication, and shuffling. Deep Learning (DL) techniques have been proven effective in analysis and processing of visual media. Dealing with video data needs to handle th

Background: Sprite coding is a very effective technique for clarifying the background video object. The sprite generation is an open issue because of the foreground objects which prevent the precision of camera motion estimation and blurs the created sprite. Objective: In this paper, a quick and basic static method for sprite area detection in video data is presented. Two statistical methods are applied; the mean and standard deviation of every pixel (over all group of video frame) to determine whether the pixel is a piece of the selected static sprite range or not. A binary map array is built for demonstrating the allocated sprite (as 1) while the non-sprite (as 0) pixels valued. Likewise, holes and gaps filling strategy was utilized to re

In this research, a new technique is suggested to reduce the long time required by the encoding process by using modified moment features on domain blocks. The modified moment features were used in accelerating the matching step of the Iterated Function System (IFS). The main disadvantage facing the fractal image compression (FIC) method is the over-long encoding time needed for checking all domain blocks and choosing the least error to get the best matched domain for each block of ranges. In this paper, we develop a method that can reduce the encoding time of FIC by reducing the size of the domain pool based on the moment features of domain blocks, followed by a comparison with threshold (the selected  threshold based on experience

There is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that

The present research deals with the study of the symmetries of the design of interior spaces in fast food restaurants in terms of formality as it is an important element and plays a direct role in the spatial configuration, which is designed in both of its performance, aesthetic and expressive aspects. Since the choice of shapes is a complex subject that has many aspects imposed by functional and aesthetic correlations, the problem of the research is represented by the following question: (To what extent can the symmetries of the interior design be used in the spaces of fast food restaurants?)
The research acquires its importance by contributing to the addition of knowledge to researchers, scholars, companies and the specialized publ

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

     This research was conducted to measure the levels of asbestos fibers in the air of some dense sites of Baghdad city, which were monitored in autumn 2019. Samples collection was conducted via directing air flow to a mixed cellulose ester membrane filter mounted on an open‑faced filter holder using sniffer with a low flow sampling pump. Air samples were collected from four studied areas selected in some high traffic areas of Baghdad city, two of them were located in Karkh (Al-Bayaa and Al-Shurta tunnel) and two in Rusafa (Al-Jadriya and Al-Meshin complex), then analyzed to determine concentrations of asbestos. Measuring of levels of asbestos fibers on the filters was carried out via using scanning electron micros

In order to select the optimal tracking of fast time variation of multipath fast time variation Rayleigh fading channel, this paper focuses on the recursive least-squares (RLS) and Extended recursive least-squares (E-RLS) algorithms and reaches the conclusion that E-RLS is more feasible according to the comparison output of the simulation program from tracking performance and mean square error over five fast time variation of Rayleigh fading channels and more than one time (send/receive) reach to 100 times to make sure from efficiency of these algorithms.