Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.

With the great development in the field of the Internet, the talk about the new media and its implications began, And its interactive services have made the future of media material sometimes participating in it and manufacturing it at other times,
the public is seeking information and choosing the appropriate ones, as well as exchanging messages with the sender after what the role of the receiver is just receiving information only.
This study aims to demonstrate the effects of using digital media in various forms and types to construct the value system of Iraqi society through the identification of the following aims:
Identify the most popular digital media for the Iraqi public in their daily lives on the Internet.
Identify

A groundwater quality assessment has been carried out in northeast part of Anbar governorate in western Iraq. We analyzed hydrochemical parameters such as pH, electrical conductivity, total dissolved solids presence of ions to describe groundwater quality. The study area has the only confined aquifer within the geological formation extended in area. Values of groundwater hydrochemical parameters were ranged from (7) to (7.9) for ph, (1599) to (6800) µmhos/cm for electrical conductivity (EC) and (1048) to (4446) mg/l for total dissolved solids (TDS). The origins and types of groundwater in the area were of marine origin and MgCl₂ water type while only (6) samples were of continental origin and Na₂SO₄ wate

The planning for the formation of administrative policies and guidance through leadership are important things for managing administrative processes and sporting activities. As both contribute in the stability of the administrative conditions, and their development in the sport federations, whether they both were attentive about team and individual Olympic Games. The two researchers observe that, there is a variation in the correct way of application. Particularly in the formulation of administrative policies and leadership describing it as, modern management standards for both team and individual Olympic Games in the Iraqi National Olympic Committee. That led to cause a misconception and lack of clarity for some administrators of those uni

Abstract:

It is essential to provide health care directly or indirectly based on laboratory tests in order of diagnosing diseases. There is an urgent need for the results of such tests to be accurate and reliable. Therefore, the International Organization for Standardization has prepared special standards for medical laboratories to prove their efficiency, presented in standards 15189: 2012. The aim of the research is to determine the possibility of the Al-alwiya Women's Hospital in meeting the requirements of the standards 15189: 2012, which includes administrative requirements consisting of fifteen items and technical requirements consisting of ten items. The research is important because laboratories shou

A nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve