<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

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

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.

A new two-way nesting technique is presented for a multiple nested-grid ocean modelling system. The new technique uses explicit center finite difference and leapfrog schemes to exchange information between the different subcomponents of the nested-grid system. The performance of the different nesting techniques is compared, using two independent nested-grid modelling systems. In this paper, a new nesting algorithm is described and some preliminary results are demonstrated. The validity of the nesting method is shown in some problems for the depth averaged of 2D linear shallow water equation.

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

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

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This study aimed to develop an oral drug delivery system for gastro-retentive sustained drug release of baclofen by using a 3D printed capsular device since baclofen has a short half-life of 2.5 to 4 hours and has a narrow absorption window. Firstly sustained-release tablets of baclofen were formulated through the hot-melt extrusion of various thermoplastic polymers and direct compression of the extrudate, then a capsular device was designed and 3D printed to contain two air pockets to enable floating of the device and has four windows for drug release.

3D printing of the capsular device was done by an FDM printer using biodegradable PLA filament, and the sustained release tablets were inserted into the device to allow the medici