Most Internet-tomography problems such as shared congestion detection depend on network measurements. Usually, such measurements are carried out in multiple locations inside the network and relied on local clocks. These clocks usually skewed with time making these measurements unsynchronized and thereby degrading the performance of most techniques. Recently, shared congestion detection has become an important issue in many computer networked applications such as multimedia streaming and
peer-to-peer file sharing. One of the most powerful techniques that employed in literature is based on Discrete Wavelet Transform (DWT) with cross-correlation operation to determine the state of the congestion. Wavelet transform is used as a de-noisin

In terms of each party's contribution to the common venture, partnership felt in several categories. It would be a complete partnership, that is, one in which all partnership, both capital and service; It could be an arrangement like the commenda (Arabic : Mudãraba , muqãraba , girãd) in which one party supplied the capital and the other service .
In Malikite and Hanaifite Law, It would take the form of a labor partnership, that is, one in which the only investment on the part of all its members was their skill or labor. In this last category of partnership, the captil itself considered solely or primarily of the labor of the partners.

In this study, the two researchers try to identify the degree of psychological flow among third-stage students in the College of Physical Education and Sports Sciences / University of Baghdad, by constructing a psychometric flow meter for third-stage students in the College of Physical Education and Sports Sciences / University of Baghdad, and the research sample reached 123 female students They represent 100% of the research community, and after conducting the scientific foundations for building the scale, the two researchers reached the final version of the psychometric flow scale with 21 items with four axes.

The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

The separation of fluid-fluid mixtures is a major issue in various sectors. The liquid-liquid hydro-cyclone has a wide range of applications in various sectors due to its great efficiency in separating fluid mixtures, ease of installation, and low cost. In crude oil production, high water is consumed following the degrading of production quality, high processing costs, costs, and environmental impacts. Axial hydro cyclone is a tool for Downhole Oil/Water Separation (DOWS) in the petroleum production industry, but it has limitations. The main purpose of this work is to simulate the effect of compacting the conventional inline hydro cyclone with a converging-diverging nozzle on the oil/water dynamic flow and the separation process to

We observed strong nonlinear absorption in the CdS nanoparticles of dimension in the range 50-100 nm when irradiant with femtosecond pulsed laser at 800 nm and 120 GW/cm 2 irradiance intensity. The repetition rate and average power were 250 kHz and