A Factorial Study for separation anxiety in students, of Baghdad City

The research aims to identify the theoretical framework of technical reserves in the insurance activity and the role of the auditor in verifying the integrity of the estimates of technical provisions (technical reserves) for the branches of general insurance in insurance companies based on the relevant international auditing standards, as a proposed audit program has been prepared in accordance with international auditing standards that enable the auditor to express a sound opinion on the fairness of the financial statements of these companies , The research has reached many conclusions, the most important of which is the existence of deficiencies in the audit procedures of insurance companies, as the audit program of those companies did

Deep Learning Techniques For Skull Stripping of Brain MR Images

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

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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.

Water saturation is the most significant characteristic for reservoir characterization in order to assess oil reserves; this paper reviewed the concepts and applications of both classic and new approaches to determine water saturation. so, this work guides the reader to realize and distinguish between various strategies to obtain an appropriate water saturation value from electrical logging in both resistivity and dielectric has been studied, and the most well-known models in clean and shaly formation have been demonstrated. The Nuclear Magnetic Resonance in conventional and nonconventional reservoirs has been reviewed and understood as the major feature of this approach to estimate Water Saturation based on T2 distribution. Artific

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.

<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