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Bond strength of a new Kevlar fiber-reinforced composite post with semi-interpenetrating polymer network (IPN) matrix
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Publication Date
Tue Dec 30 2025
Journal Name
Journal Of Baghdad College Of Dentistry
The effect of plasma treatment on shear bond strength of soft denture liner with two different types of denture base material (heat cure and light cure)
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Background: In this study we evaluate the effect of plasma treatment (oxygen and argon) gas in two different exposure times on the surface of heat cure and light cure acrylic resin. Materials and method: 100 specimens of heat cure and light cure acrylic resin were fabricated. The measurements of the samples were (75mm, 25mm and 4.5mm) length, width and depth respectively with stopper of 3mm depth. Two types of gas used oxygen and argon in (5,10) min by using (DC-glow discharge plasma device) then we apply cold cure soft lining material, with the help of Instron machine we test the shear stress value. Results: A highly significant effect after argon and oxygen gases treatment in both 5 and 10 min exposure times on shear bond strength to soft

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Strengthening and Closing Cracks for Existing Reinforced Concrete Girders Using Externally Post-Tensioned Tendons
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This research is devoted to study the strengthening technique for the existing reinforced concrete beams using external post-tensioning. An analytical methodology is proposed to predict the value of the effective prestress force for the external tendons required to close cracks in existing beams. The external prestressing force required to close cracks in existing members is only a part from the total strengthening force.
A computer program created by Oukaili (1997) and developed by Alhawwassi (2008) to evaluate curvature and deflection for reinforced concrete beams or internally prestressed concrete beams is modified to evaluate the deflection and the stress of the external tendons for the externally strengthened beams using Matlab

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Publication Date
Mon Nov 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Solution of Riccati matrix differential equation using new approach of variational ‎iteration method
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To obtain the approximate solution to Riccati matrix differential equations, a new variational iteration approach was ‎proposed, which is suggested to improve the accuracy and increase the convergence rate of the approximate solutons to the ‎exact solution. This technique was found to give very accurate results in a few number of iterations. In this paper, the ‎modified approaches were derived to give modified solutions of proposed and used and the convergence analysis to the exact ‎solution of the derived sequence of approximate solutions is also stated and proved. Two examples were also solved, which ‎shows the reliability and applicability of the proposed approach. ‎

Publication Date
Mon Dec 01 2025
Journal Name
Case Studies In Construction Materials
Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms
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Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia

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Publication Date
Mon Jun 20 2022
Journal Name
Nano Hybrids And Composites
Fabrication and Characterization of Functionalized Multi-Wall Carbon Nanotubes Flexible Network Modified by a Layer of Polypyrrole Conductive Polymer and Metallic Nanoparticles
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Short Multi-Walled Carbon Nanotubes functionalized with OH group (MWCNTs-OH) were used to synthesize flexible MWCNTs networks. The MWCNTs suspension was synthesized using Benzoquinone (BQ) and N, N Dimethylformamide alcohol (DMF) in specific values and then deposited on filter paper by filtration from suspension (FFS) method. Polypyrrole (PPy) conductive polymer doped with metallic nanoparticles (MNPs) prepared using in-situ chemical polymerization method. To improve the properties of the MWCNTs networks, a coating layer of (PPy) conductive polymer, PPy:Ag nanoparticles, and PPy: Cu nanoparticles were applied to the network. The fabricated networks were characterized using an X-ray diffractometer (XRD), UV-Vis. spectrometer, and Ato

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Publication Date
Fri Oct 01 2021
Journal Name
Civil Engineering Journal
Steel Fiber Enhancement upon Punching Shear Strength of Concrete Flat Plates Exposed to Fire Flame
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In this study, the effect of fire flame on the punching shear strength of steel fiber reinforced concrete flat plates was experimentally investigated using nine half-scale specimens with dimensions of 1500×1500 mm and a total thickness of 100 mm. The main investigated variables comprised the steel fiber volume fraction 0, 1, and 1.5% and the burning steady state temperature 500 and 600 °C. The specimens were divided into three groups, each group consists of three specimens. The specimens in the first group were tested with no fire effect to be the reference specimens, while the others of the second and third groups were tested after being exposed to fire-flame effect. The adopted characteristics of the fire test were; (one hour) b

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Publication Date
Fri Jan 31 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
A comparative study to evaluate the effect of ultrasonic agitation on push-out bond strength of three root-end filling materials: An in vitro study
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Aim: To evaluate the effect of ultrasonic agitation for retrograde biodceramic root repair, MTA and biodentine filling materials on push-out bond strength to dentine walls. Materials and Methods: Ninety extracted human teeth with single straight roots were selected randomly. After disinfection and cleaning, the coronal portions were sectioned to standardize the root canal length at 15mm. following root canal shaping, obturation and apical roots resection, retrograde cavities were prepared. Teeth were categorized depending on the filling material used into three groups, 30 teeth each. Group A filled with bioceramic root repair material, B with MTA and C with Biodentine material. These groups were divided in to three subgroup (n= 10). Subgrou

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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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Publication Date
Fri Jan 01 2016
Journal Name
Computational Intelligence And Neuroscience
A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)
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This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl

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