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

High peak to average power ration (PAPR) in orthogonal frequency division multiplexing (OFDM) is an important problem, which increase the cost and complexity of high power amplifiers. One of the techniques used to reduce the PAPR in OFDM system is the tone reservation method (TR). In our work we propose a modified tone reservation method to decrease the PAPR with low complexity compared with the conventional TR method by process the high and low amplitudes at the same time. An image of size 128×128 is used as a source of data that transmitted using OFDM system. The proposed method decrease the PAPR by 2dB compared with conventional method with keeping the performance unchanged. The performance of the proposed method is tested with

A simulation study of using 2D tomography to reconstruction a 3D object is presented. The 2D Radon transform is used to create a 2D projection for each slice of the 3D object at different heights. The 2D back-projection and the Fourier slice theorem methods are used to reconstruction each 2D projection slice of the 3D object. The results showed the ability of the Fourier slice theorem method to reconstruct the general shape of the body with its internal structure, unlike the 2D Radon method, which was able to reconstruct the general shape of the body only because of the blurring artefact, Beside that the Fourier slice theorem could not remove all blurring artefact, therefore, this research, suggested the threshold technique to eliminate the

Peak ground acceleration (PGA) is one of the critical factors that affect the determination of earthquake intensity. PGA is generally utilized to describe ground motion in a particular zone and is able to efficiently predict the parameters of site ground motion for the design of engineering structures. Therefore, novel models are developed to forecast PGA in the case of the Iraqi database, which utilizes the particle swarm optimization (PSO) approach. A data set of 187 historical ground-motion recordings in Iraq’s tectonic regions was used to build the explicit proposed models. The proposed PGA models relate to different seismic parameters, including the magnitude of the earthquake (Mw), average shear-wave velocity (VS30), focal depth (FD

Artificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa

Activity test of the inhibitors purified from barley and broad beans crop proved the inhibition activity against 6 types of rots Pencillium ssp and Aspergellusflavus and Aspergillus niger and Fusarium solani and Fusarium semitectum and Mucor with three concentrations 0.1 and 0.2 and 0.3 mg/ml, where the inhibitor purified from the second peak of broad beans proved that it had a higher inhibition activity against the growth of test rots which were 53.75 and 62.5 and 78.5 and 76.25 and 84 and 18.8% respectively, at 0.3 mg/ ml followed by the first peak of the inhibitor purified from broad beans the inhibition activity were 43.75 and 50 and 62.96 and 75 and 80 and 12.5 then the inhibitor purified from barley in which the inhibition activity

Background: Gotu Kola (Centella asiatica) has been used as a traditional medicine for many years to cure different kinds of diseases. Studies have been reported that Gotu Kola extracts might be used as a cure for oral diseases such as periodontal disease. In the present study, Gotu Kola leaves extracted with water will be used to evaluate its effect on some microorganisms living in the human saliva using minimum inhibitory concentration (MIC) method. Material and Method:Gotu Kola fresh leaves extract have been used with water as a solvent, a rotary evaporator was used to separate the solvent from the extract. The following microorganisms: Streptococci, Lactobacilli, and Staphylococcus aureus have been isolated fromthe Saliva of ten voluntee