The psychological scientific studies suggest that basic human situations stem from human emotional abilities and those with a lack of emotional intelligence are unable to cope with life, which might lead to anxiety and psychological depression. The current study aimed to investigate this problem by identifying the level of emotional intelligence and psychological depression among the students of the University of Anbar. To achieve the objectives of the study, the researchers created two questionnaires: 1) to measure emotional intelligence. 2) to measure psychological depression and applied these questionnaires on (300) students. The results revealed that the participants showed a high level of emotional intelligence with a low level of p

This study aims to identify the forgiveness level among gifted students and its relation to the self-awareness. The study sample consisted of (207) students were randomly chosen, they are integrated in secondary schools in Abha / Saudi Arabia. The correlative, analytical descriptive method was adopted. Two scales were adopted by the researcher: The forgiveness scale prepared by Rye et al (2001) which translated to Arabic by Al-Mahasneh (2017) and the self-awareness scale which prepared by Al-Ghezwani (2017). The study results indicated the following: the forgiveness level among the talented students was high, the self-awareness level among talented students was high, and there is a positive statistically significant relationship

Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .

                In this paper  a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering  and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet

In this paper, the Mars orbital elements were calculated. These orbital elements—the major axis, the inclination (i), the longitude of the ascending node (W), the argument of the perigee (w), and the eccentricity (e)—are essential to knowing the size and shape of Mars' orbit. The quick basic program was used to calculate the orbital elements and distance of Mars from the Earth from 25/5/1950 over 10000 days. These were calculated using the empirical formula of Meeus, which depended on the Julian date, which slightly changed for 10000 days; Kepler's equation was solved to find Mars' position and its distance from the Sun. The ecliptic and equatorial coordinates of Mars were calculated. The distance between Mars and the center of the E

An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

One of the challenges faced by traditional intrusion detection systems based on machine learning or deep learning is instability when dealing with unbalanced network traffic, leading to failure in detecting certain attacks (minority classifications). Additionally, they struggle with multi-stage attacks, resulting in an increase in false alarms. This paper presents a hierarchical intrusion detection system supported by a Prediction Verification Layer (PVL) and a Feature Inheritance Mechanism (FIM). Where PVL contributes to documenting the system’s final decision and increasing sensitivity to minority attacks, FIM also helps in inheriting features from previous layers and correcting errors as much as possible. Additionally, it allows for ad