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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 partially replaced by ground granulated blast furnace slag (GGBFS) with various amounts to make the concrete eco-friendly. The concrete was reinforced with several quantities of PP fiber. Specific cases of beams and cylinders made from PFRC were examined to learn more about their performance. The research contributes valuable insights to eco-friendly concrete design by integrating industrial byproducts (GGBFS) and non-metallic fibers, aligning with sustainable construction trends. The study demonstrates that adding sustainable fibers to concrete improves its structural integrity while lessening its environmental impact. Experimental testing validates the proposed model, showing a significant connection between the expected and actual stress-strain behavior. In terms of absolute relative error (ARE), the dataset proves that the suggested model has both the greatest (ARE 5 %) and worst (ARE > 15 %) frequencies. The proposed model demonstrates promising accuracy (R-value = 0.9975) and highlights the effectiveness of PSO in parameter optimization. Additionally, the usage of GGBFS instead of OPC resulted in CO2 reduction up to 42 %. Comparative analysis of the proposed model against existing models registered an excellent forecasted accuracy.

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
MECHANISTIC EVALUATION OF LIME-MODIFIED ASPHALT CONCRETE MIXTURES
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Frequently, Load associated mode of failure (rutting and fatigue) as well as, occasionally, moisture damage in some sections poorly drained are the main failure types found in some of the newly constructed road within Baghdad as well as other cities in Iraq. The use of hydrated lime in pavement construction could be one of the possible steps taken in the direction of improving pavement performance and meeting the required standards. In this study, the mechanistic properties of asphalt concrete mixes modified with hydrated lime as a partial replacement of limestone dust mineral filler were evaluated. Seven replacement rates were used; 0,0.5, 1, 1.5, 2, 2.5 and 3 percent by weight of aggregate. Asphalt concrete mixes were prepared at their

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Publication Date
Mon Feb 01 2021
Journal Name
Meta Gene
Association analysis of FTO gene polymorphisms rs9939609 and obesity risk among the adults: A systematic review and meta-analysis
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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
A Software Defined Network of Video Surveillance System Based on Enhanced Routing Algorithms
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Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we eva

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Engineering
Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

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Publication Date
Wed Jan 01 2014
Journal Name
Journal Of Biology And Life Science
Newcastle Disease Virus (NDV) Iraqi Strain AD2141 Induces DNA Damage and FasL in Cancer Cell Lines
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The oncolytic viruses are promising form of cancer therapy which is based on the selectively killing of the cancer cells. This study was aimed to investigate the role of Newcastle disease virus (NDV) Iraqi strain AD2141 in apoptosis. Firstly, the virulence of AD2141 was detected in embryonated chicken eggs after 48hrs of infection. It was observed a hemorrhage in the skin of infected embryos that led to death. Then, the ability of this strain for regression cancer cell lines was examined. By using cytotoxicity test, it was found 128 HAU/ml of AD2141 had a potent inhibition against growth of RD and AMN3 after 72hrs of exposure time; the inhibition rate was 86.8% and 86.98% respectively. Moreover, the apoptotic activity of AD2141 was exami

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
Stress and Its Impact on Mental and Physical Health
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Stress is an inevitable part of life. Stress occurs when stressful events of self, environmental, or social origin affect the individual's resilience and threaten to collapse his psychological and physical systems. The stress represents difficulties and obstacles that may exceed the individual's ability to bear them and deal with them, which causes him stress and causes negative effects on his psychological and physical health. Therefore, the current research aimed to identify the negative effects of psychological stress on the psychological and physical health of the individual through the literature that dealt with this topic. It was among the results of the research that one of the negative effects of stresses on mental health is the

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Publication Date
Mon Apr 19 2021
Journal Name
Bridge Maintenance, Safety, Management, Life-cycle Sustainability And Innovations
Flexure strengthening of concrete bridge girders with concavely curved soffit using near-surface-mounted CFRP bars
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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Bridge Engineering
Torsional Analysis of Multicell Concrete Box Girders Strengthened with CFRP Using a Modified Softened Truss Model
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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Chemical sensor based on a solid-core photonic crystal fiber interferometer
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Photonic crystal fiber interferometers are used in many sensing applications. In this work, an in-reflection photonic crystal fiber (PCF) based on Mach-Zehnder (micro-holes collapsing) (MZ) interferometer, which exhibits high sensitivity to different volatile organic compounds (VOCs), without the needing of any permeable material. The interferometer is robust, compact, and consists of a stub photonic crystal fiber of large-mode area, photonic crystal fiber spliced to standard single mode fiber (SMF) (corning-28), this splicing occurs with optimized splice loss 0.19 dB In the splice regions the voids of the holey fiber are completely collapsed, which allows the excitation and recombination of core and cladding modes. The device reflection

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Publication Date
Thu Feb 29 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Design and Development of Powerful Neuroevolution Based Optimized GNNBiLSTM Model for Consumer Behaviour and Effective Recommendation in Social Networks
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