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

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

Wellbore instability is one of the most common issues encountered during drilling operations. This problem becomes enormous when drilling deep wells that are passing through many different formations. The purpose of this study is to evaluate wellbore failure criteria by constructing a one-dimensional mechanical earth model (1D-MEM) that will help to predict a safe mud-weight window for deep wells. An integrated log measurement has been used to compute MEM components for nine formations along the studied well. Repeated formation pressure and laboratory core testing are used to validate the calculated results. The prediction of mud weight along the nine studied formations shows that for Ahmadi, Nahr Umr, Shuaiba, and Zubair formations

Since the introduction of the HTTP/3, research has focused on evaluating its influences on the existing adaptive streaming over HTTP (HAS). Among these research, due to irrelevant transport protocols, the cross-protocol unfairness between the HAS over HTTP/3 (HAS/3) and HAS over HTTP/2 (HAS/2) has caught considerable attention. It has been found that the HAS/3 clients tend to request higher bitrates than the HAS/2 clients because the transport QUIC obtains higher bandwidth for its HAS/3 clients than the TCP for its HAS/2 clients. As the problem originates from the transport layer, it is likely that the server-based unfairness solutions can help the clients overcome such a problem. Therefore, in this paper, an experimental study of the se

The objective of the research is to evaluate the risk management practices of the variables (risk management structure, risk management methods, key components of risk management) and their relation to the principled behavior of managers behavior(innovation, proactive, risk acceptance) By adopting the questionnaire as a main tool in collecting data from managers in the National and raq insurance companies of (50) officials Department manager, department administrator, unit administrator, and analyzed their answers using the SPSS In calculating arithmetic mean, standard deviation, percentage weight and simple correlation coefficient. The most prominent conclusions were:1.There is a positive trend in the sample in both companies and a high

Abstract

Purpose of this study is to investigate the relationship between Advertising Appeals, Attitudes toward Advertising, and Consumer Buying Behavior for Smart Phone The study was carried out on the students of Middle East University (MEU) In Amman- Jordan.  A measurement scales  with acceptable reliability and validity is developed to capture the dimensions of study variables.  Four hypotheses were tested using Statistical package (SPSS-17).  A two-step detailed statistical analysis of data was involved. First, descriptive statistics was performed to understand the underlying components of study variables; second, regression analysis and Path analysis using AMOS 7 were performed t

Density Functional Theory (DFT) calculations were carried out to study the thermal cracking for acenaphthylene molecule to estimate the bond energies for breaking C8b-C5a , C5a-C5 , C5-C4 , and C5-H5 bonds as well as the activation energies. It was found that for C8b-C5a , C5-C4 , and C5-H5 reactions it is often possible to identify one pathway for bond breakage through the singlet or triplet states. The atomic charges , dipole moment and nuclear – nuclear repulsion energy supported the breakage bond .Also, it was found that the activation energy value for C5-H5 bond breakage is lower than that required for C8b-C5a , C5a-C5 , C5-C4 bonds which refer to C5-H5 bond in acenaphthylene molecule are weaker than C8b-C5a , C5a-C5 , C5-C

The consumption of fresh fruits has increased nowadays due to the lifestyle of the consumers. Maintaining the quality and nutritional value of cut fruits during storage is difficult compared to whole fruits. Deterioration of internal and external quality usually occurs in freshly harvested fruits. It is necessary to use different techniques to maintain the quality and increase the shelf life of the freshly cut product. This research studied the effect of treating apple slices with cold plasma once and with filtered water again on quality characteristics (hardness, moisture content, sugar content, carbohydrate content, and color) after being stored for five days. The best treatment was determined using two different pressures of the plasma j

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo