Abstract

The aim of the present work is to control of metal buried corrosion by alteration the media method. This method depended on the characteristics of each media. The corrosion rates in different media (soil, sand, porcelanite stone and gravel) for specimens of low carbon steel were measured by two methods weight loss method and polarization method, weight loss measured by buried specimens in these medias separately for 90 days. The polarization method includes preparing of specimen and salt solutions have electrical resistivity equivalent electrical resistivity of these media. The corrosion rate of two method results in (soil > sand> porcelainte stone> gravel). The lower corrosion rate happene

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

Green nanotechnology is a thrilling and rising place of technology and generation that bracesthe ideas of inexperienced chemistry with ability advantages for sustainability, protection, andthe general protection from the race human. The inexperienced chemistry method introduces aproper technique for the production, processing, and alertness of much less dangerous chemicalsubstances to lessen threats to human fitness and the environment. The technique calls for inintensity expertise of the uncooked materials, particularly in phrases in their creation intonanomaterials and the resultant bioactivities that pose very few dangerous outcomes for peopleand the environment. In the twenty-first century, nanotechnology has become a systematic

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

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

Improving students’ use of argumentation is front and center in the increasing emphasis on scientific practice in K-12 Science and STEM programs. We explore the construct validity of scenario-based assessments of claim-evidence-reasoning (CER) and the structure of the CER construct with respect to a learning progression framework. We also seek to understand how middle school students progress. Establishing the purpose of an argument is a competency that a majority of middle school students meet, whereas quantitative reasoning is the most difficult, and the Rasch model indicates that the competencies form a unidimensional hierarchy of skills. We also find no evidence of differential item functioning between different scenarios, suggesting

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

Laser assisted skin wound closure offers many distinct advantages over conventional closure
techniques. The objective of this in vitro experimental study, carried out at the Institute of Laser for
Postgraduate Studies/Baghdad University, was to determine the effectiveness of 980 nm diode laser in
welding of human skin wounds. Multiple 3-4 cm long full thickness incisions in a specimen of human
skin obtained from the discarded panniculus of an Abdominoplasty operation were tried to be laser
welded using a 4 mm spot diameter laser beam from a 980 nm diode laser at different laser parameters
and modes of action. The tensile strength at the weld site was analyzed experimentally. Although laser
assisted wound welding did

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol