Image compression is a serious issue in computer storage and transmission,  that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the  mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com

Worldwide, enormous amounts of waste cause major environmental issues, including scrap tires and plastic, and large waste, a consequence of the demolition of buildings, including crushed concrete, crushed clay bricks, and crushed thermo-stone. From that point, it’s possible to consider that the recycling processes for these materials and using them in the manufacturing field will reduce the adverse effects on the environment of these wastes and the consumption of natural resources. Sustainable concrete blocks can be considered as one of the products produced by using these materials as partial volume replacement of the coarse, fine aggregate, or cement content, considering their dry density, workability, absorption, co

Worldwide, enormous amounts of waste cause major environmental issues, including scrap tires and plastic, and large waste, a consequence of the demolition of buildings, including crushed concrete, crushed clay bricks, and crushed thermo-stone. From that point, it’s possible to consider that the recycling processes for these materials and using them in the manufacturing field will reduce the adverse effects on the environment of these wastes and the consumption of natural resources. Sustainable concrete blocks can be considered as one of the products produced by using these materials as partial volume replacement of the coarse, fine aggregate, or cement content, considering their dry density, workability, absorption, compressive st

As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .

This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others

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