The important device in the Wireless Sensor Network (WSN) is the Sink Node (SN). That is used to store, collect and analyze data from every sensor node in the network. Thus the main role of SN in WSN makes it a big target for traffic analysis attack. Therefore, securing the SN position is a substantial issue. This study presents Security for Mobile Sink Node location using Dynamic Routing Protocol called (SMSNDRP), in order to increase complexity for adversary trying to discover mobile SN location. In addition to that, it minimizes network energy consumption. The proposed protocol which is applied on WSN framework consists of 50 nodes with static and mobile SN. The results havw shown in each round a dynamic change in the route to reach mobi

Although renewable energy systems have become an interesting global issue, it is not continuous either daily or seasonally. Latent heat energy storage (LHES) is one of the suitable solutions for this problem. LHES becomes a basic element in renewable energy systems. LHES compensate for the energy lack when these systems are at low production conditions. The present work considered a shell and tube LHES for numerical investigation of the tube rotation influence on the melting process. The simulation and calculations were carried out using ANSYS Fluent software. Paraffin wax represents the phase change material (PCM) in this work, while water was selected to be the heat transfer fluid (HTF). The calculations were carried o

The research objective was to study the amount of lost fluids, some blood components and mineral salts in volleyball players under hot weather conditions. The sample of the present study was composed of 12 volleyball players of Al-Sinaa Club (Baghdad, Iraq) in the 2022/2023 season. The variables analyzed in this study were: Heart rate before and after exercise, internal and external body temperature before and after exertion, potassium ion, sodium ion, calcium ion, and the amount of fluid lost (the player's weight) before and after the exercise. The tests were conducted at a temperature between 42-47 degrees Celsius. The maximum anaerobic exercise was performed with volleyball. The results showed that to play volleybal

The research objective was to study the amount of lost fluids, some blood components and mineral salts in volleyball players under hot weather conditions. The sample of the present study was composed of 12 volleyball players of Al-Sinaa Club (Baghdad, Iraq) in the 2022/2023 season. The variables analyzed in this study were: Heart rate before and after exercise, internal and external body temperature before and after exertion, potassium ion, sodium ion, calcium ion, and the amount of fluid lost (the player's weight) before and after the exercise. The tests were conducted at a temperature between 42-47 degrees Celsius. The maximum anaerobic exercise was performed with volleyball. The results showed that to play volleybal

in this paper fourth order kutta method has been used to find the numerical solution for different types of first liner

In this study, the performance of the adaptive optics (AO) system was analyzed through a numerical computer simulation implemented in MATLAB. Making a phase screen involved turning computer-generated random numbers into two-dimensional arrays of phase values on a sample point grid with matching statistics. Von Karman turbulence was created depending on the power spectral density. Several simulated point spread functions (PSFs) and modulation transfer functions (MTFs) for different values of the Fried coherent diameter (r_o) were used to show how rough the atmosphere was. To evaluate the effectiveness of the optical system (telescope), the Strehl ratio (S) was computed. The compensation procedure for an AO syst

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m