The present paper aims at finding out the Variance Ratio of Trips Set Out by Scholars of Both Marrouzzeen and Baihaq  .The researcher has come up with conclusion including certain findings ,one of which is that the trip is considered an essential base with high effectiveness since  the old times and has been evolved .This means that the trip has been the main source of  knowledge and sciences from the scholars directly .This had driven the scholars of both Baihaq and Marrouz cities .It has been noticed , though this paper, that the number of the Marrouz scholars who visited was less than those of Baihaq . The researcher has focused on their meetings or conferences and investigated what has been going on in such meetin

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

The grain hardness, wet and dry gluten contents, protein and ash contents are determined in grains from different cultivars of wheat which are important in food products, either which are present in raw materials or in final products. Wheat is also a very important food raw material, and flour as the final product of milling. The importance of knowing the physical and chemical properties of wheat and flour is due to the determination of quality and kind of flour which is produced after the milling process. In this work, some physical and chemical properties of different wheat cultivars are determined and the comparisons of these characteristics are performed in both wheat and flour. Uruq Wheat sample (W5) has the highest results when compar

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

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Although severe epistaxis is uncommon, it is serious. The systematic endoscopic nasal examination is an essential step in identifying the bleeding point and aiding electrocauterization. Currently, the S-point, which is located in the superior part of the nasal septum behind the septal body and corresponding to the axilla of the middle concha, is identified in about 30% of cases with severe epistaxis. Cauterization of this point has an excellent rate of controlling the bleeding and preventing its recurrence. We aimed to highlight the significance of the S-point in the management of severe cases of epistaxis.