Today’s world confronts various threats from different sources. Similar to deprivation of energy, economic facilities, or political deposition, educational poisoning is one of the dangerous phenomena that result from distorting and corrupting the ethical and educational components of teaching by various material and non – material means.This paper sheds light on the concept of the educational system which is not a mere process of teaching, but rather an endless process of socialization that begins in the family and develops into religious, ethical, scientific and mythological systems, all of which form the cognitive component. It also defines the necessary means by which it is transmitted from one generation into another. The educati

The research team seeks to study the phenomena of random housing in Iraqi society in general and Baghdad city in particular by standing on the causes behind this phenomena and its relation with security situation in Baghdad. The researchers adopted a theoretical and practical framework. The main objective is to diagnose the risks caused by the escalation of slums in Baghdad city. 

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

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

Measuring university teachers attitudes towards the security man Summary This research aims to study the measurement of university teachers attitudes towards the security man, and represented the research sample (196) of teachers, including 124 males and 72 females from different faculties of Salah al-Din - Erbil University. The researchers adopted on a scale (Al-Tarawneh 2008), as amended, and its development, the scale consists of four areas and (28) paragraph covers paragraphs measure the beliefs and feelings of the individual towards the security man as the theme of direction. The research sample answered all the paragraphs of the scale grade five similar styles (Likert) (strongly OK, OK, neutral, non-OK, Strongly Disagree). The rese

Modern sports clubs in Baghdad are in urgent need of adopting advanced technologies to enhance the efficiency of their operational and administrative processes. Among the most prominent of these technologies is cloud computing, which offers flexible and cost effective solutions for data storage and application management. However, sports clubs in Baghdad face significant challenges in adopting this technology, manifested in technical and administrative obstacles that limit the full utilization of cloud computing capabilities. The research problem lies in identifying and analyzing these obstacles, with the aim of providing a comprehensive understanding of the challenges faced by sports clubs in Baghdad. Sports clubs deal with a huge amount o

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

The growing interest in the use of chaotic techniques for enabling secure communication in recent years has been motivated by the emergence of a number of wireless services which require the service provider to provide low bit error rates (BER) along with information security. This paper investigates the feasibility of using chaotic communications over Multiple-Input-Multiple-Output (MIMO) channels. While the use of Chaotic maps can enhance security, it is seen that the overall BER performance gets degraded when compared to conventional communication schemes. In order to overcome this limitation, we have proposed the use of a combination of Chaotic modulation and Alamouti Space Time Block Code. The performance of Chaos Shift Keying (CSK) wi