Extracting, studying and interpreting the morphological database of a basin is a basic building block for building a correct geomorphological understanding of this basin. In this work, Arc GIS 10.8 software and SRTM DEM satellite images were used. The principle of data integration was adopted by extracting the quantitative values of the morphometric characteristics that are affected by the geomorphological condition of the studied basin, then eliciting an optimal conception of the geomorphological condition of the basin from the meanings and connotations of these combined transactions. Hypsometric integration was extracted for each region in the basin separately with the value of integration of the plot curve for the relative heights of

Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

Construction is a complicated process that takes place in an almost uncontrollable environment. Although projects can be carefully planned in advance in principle, there is a chance that unforeseen events and crises can disrupt these plans, affecting project development. Because the initial investment expenditures in construction projects are so large, they may be quickly influenced by crises, resulting in significant financial losses. The 2014 financial crisis was one of the most prominent crises that Iraq faced, which significantly impacted various activities in general and the construction industry in particular. Despite the importance of crisis management systems, the researchers found a great lack of local studies l

publishing has become a large space in the field of interactive education and modern pages have become dedicated to the service of the educational effort in this area as the research in this context of the urgent scientific necessities, especially as we consider in Iraq from the new countries in the exploitation of these new technologies and investment possibilities of the information network And the contents of different in the framework of so-called distance education Here lies the problem of research in the possibility of finding scientific solutions for the design of interactive inter active website for students of the preparatory stage in Iraq and to find out the scientific ways to find design The study, which included the problem of

Insufficient and poor sleep quality significantly impacts the health and quality of life of persons with end-stage renal failure (ESRF) on hemodialysis. This study explored the effectiveness of teaching patients on hemodialysis, Benson’s relaxation technique. Seventy-one persons on hemodialysis in Iraq were randomly assigned to either the experimental or the control group. The experimental group received training and encouragement to use the Benson relaxation technique. The Pittsburgh Sleep Quality Index (PSQI) score was collected for all the patients before and after the intervention. After 8 weeks a repeated measurement of the post-test on sleep quality was done for both groups. The experimental group showed a statistically sign

Micro metal forming has an application potential in different industrial fields. Flexible tool-assisted sheet metal forming at micro scale is among the forming techniques that have increasingly attracted wide attention of researchers. This forming process is a suitable technique for producing micro components because of its inexpensive process, high quality products and relatively high production rate. This study presents a novel micro deep drawing technique through using floating ring as an assistant die with flexible pad as a main die. The floating ring designed with specified geometry is located between the process workpiece and the rubber pad. The function of the floating ring in this work is to produce SS304 micro cups with profile

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an