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Thermo Elastic Analysis of Carbon Nanotube-Reinforced Composite Cylinder Utilizing Finite Element Method with the Theory of Elasticity
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Publication Date
Sun Dec 07 2014
Journal Name
Baghdad Science Journal
Corrosion Behavior of Copper and Carbon Steel in Acidic Media
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The corrosion behavior of copper and carbon steel in 1M concentration of hydrochloric acid (HCl) and sulphuric acid (H2SO4) has been studied. The corrosion inhibition of copper and carbon steel in 1M concentration of hydrochloric acid (HCl) and sulphuric acid (H2SO4) by Ciprofloxacin has been investigated. Specimens were exposed in the acidic media for 7 hours and corrosion rates evaluated by using the weight loss method. The effect of temperature (from 283 ºK to 333 ºK), pH (from 1to 6), inhibitor concentration (10-4 to 10-2) has been studied. It was observed that sulphuric acid environment was most corrosive to the metals because of its oxidizing nature, followed by hydrochloric acid. The rate of metal dissolution increased with incre

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Studying the Effect of Volume Fraction of Glass Fibers on the Thermal Conductivity of the Polymer Composite Materials
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In this study the effect of fiber volume fraction of the glass fiber on the thermal conductivity of the polymer composite material was studied. Different fiber volume fraction of glass fibers were used (3%, 6%, 9%, 12%, and 15%). Specimens were made from polyester which reinforced with glass fibers .The fibers had two arrangements according to the direction of the thermal flow. In the first arrangement the fibers were parallel to the direction of the thermal flow, while the second arrangement was perpendicular; Lee's disk method was used for testing the specimens. The experimental results proved that the values of the thermal conductivity of the specimens was higher when the fibers arranged in parallel direction than that when the fibers

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Publication Date
Fri Sep 01 2017
Journal Name
Journal Of Engineering
Fire Flame Influence on the Behavior of reinforced Concrete Beams Affected by Repeated Load
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The influence and hazard of fire flame are one of the most important parameters that affecting the durability and strength of structural members. This research studied the influence of fire flame on the behavior of reinforced concrete beams affected by repeated load. Nine self- compacted reinforced concrete beams were castellated, all have the same geometric layout (0.15x0.15x1.00) m, reinforcement details and compressive strength (50 Mpa). To estimate the effect of fire flame disaster, four temperatures were adopted (200, 300, 400 and 500) oC and two method of cooling were used (graduated and sudden). In the first cooling method, graduated, the tested beams were leaved to cool in air while in the second method, sudden, water splash was use

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Publication Date
Fri Feb 01 2019
Journal Name
International Journal Of Mechanical Engineering And Technology (ijmet)
INVESTIGATION THE PROPERTIES OF SILICONE RUBBER BLEND REINFORCED BY NATURAL NANOPARTICLES AND UHMWPE FIBER
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Many faces are exposed to degradation, discoloration, changes in humidity. The primary objective has improved some properties of hybrid nanocomposites materials that used for restoring of the function maxillofacial prosthesis and improving the esthetic. In the present research different lengths chopped and continuous of ultrahigh molecular weight polyethylene (UHMWPE) fiber was added at selected percentage (0.0, 0.2% and 1%) to polymer blend composite (95%SR /5%PMMA: 0.2% Pomegranate Peels Powder (PPP)) for developing the properties of silicone rubber used for the maxillofacial prosthesis applications. Some mechanical and physical properties were done on the all prepared samples. The results showed that all properties have improved when add

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Scopus
Publication Date
Tue Sep 19 2017
Journal Name
Journal Of Engineering
Fire Flame Influence on the Behavior of reinforced Concrete Beams Affected by Repeated Load
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The influence and hazard of fire flame are one of the most important parameters that affecting the durability and strength of structural members. This research studied the influence of fire flame on the behavior of reinforced concrete beams affected by repeated load. Nine self- compacted reinforced concrete beams were castellated, all have the same geometric layout (0.15x0.15x1.00) m, reinforcement details and compressive strength (50 Mpa).

To estimate the effect of fire flame disaster, four temperatures were adopted (200, 300, 400 and 500) oC and two method of cooling were used (graduated and sudden). In the first cooling method, graduated, the tested beams were leaved to cool in air while in the seco

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Publication Date
Mon Jan 29 2024
Journal Name
Polymer Bulletin
An experimental study to investigate the effect of aluminum nanorod-reinforced epoxy matrix nanocomposites
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Scopus (1)
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Publication Date
Wed Sep 01 2021
Journal Name
Computers And Concrete
Improving the seismic performance of reinforced concrete frames using an innovative metallic-shear damper
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Scopus (9)
Scopus
Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Image And Graphics
Normalized-UNet Segmentation for COVID-19 Utilizing an Encoder-Decoder Connection Layer Block
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The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre

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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach
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Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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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

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