The child spends several hours watching animated films, which affect their behavior negatively and positively. This calls parents to monitor what their children are watching, to show them the serious risks of some violent films, and to direct them toward choosing both positive and educational programs that develop their positive behavior. This study aimed to explore the positive and negative effects of watching animation films as well as to identify the role animation films in increasing the cognitive knowledge of kindergarteners. To do this, the descriptive and analytical methods were used. A questionnaire was adopted as a tool for data collection. A scale of (45) items classified into three categories was applied on  the r

<span>We present the linearization of an ultra-wideband low noise amplifier (UWB-LNA) operating from 2GHz to 11GHz through combining two linearization methods. The used linearization techniques are the combination of post-distortion cancellation and derivative-superposition linearization methods. The linearized UWB-LNA shows an improved linearity (IIP3) of +12dBm, a minimum noise figure (NF_min.) of 3.6dB, input and output insertion losses (S₁₁ and S₂₂)  below -9dB over the entire working bandwidth, midband gain of 6dB at 5.8GHz, and overall circuit power consumption of 24mW supplied from a 1.5V voltage source. Both UWB-LNA and linearized UWB-LNA designs are

Hiding technique for dynamic encryption text using encoding table and symmetric encryption method (AES algorithm) is presented in this paper. The encoding table is generated dynamically from MSB of the cover image points that used as the first phase of encryption. The Harris corner point algorithm is applied on cover image to generate the corner points which are used to generate dynamic AES key to second phase of text encryption. The embedded process in the LSB for the image pixels except the Harris corner points for more robust. Experimental results have demonstrated that the proposed scheme have embedding quality, error-free text recovery, and high value in PSNR.

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

CR-39 is a solid state nuclear track detector (SSNTD) that has been used in many research areas. In spite of the assumption that the CR-39 detectors are insensitive to beta and gamma rays, irradiation with these rays can have significant effects on the detector properties. In this study, beta and gamma rays mass attenuation coefficients μ/ρ (cm2 g-1) for the CR-39 detector have been measured using NaI(Tl) scintillation spectrometer along with a standard geometrical arrangement in the energy region of (0.546-2.274) MeV beta rays and standard gamma sources having energy 0.356, 0.5697, 0.6617 and 1.063 MeV. The total atomic cross-section (σtot), total electronic cross-section (σT E) and the effective atomic number (Zeff) of gamma rays a