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Utilizing Soft Computing Techniques to Estimate the Axial Permanent Deformation of Asphalt Concrete
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Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R2 of 0.93 and a mean squared error (MSE) of 0.0039. Results based on the sensitivity analysis and variable importance techniques showed that the percentage of aggregate passing the 4.75 mm sieve and the (rice) theoretical maximum specific gravity (Gmm) were the most significant factors in predicting axial permanent strain (εp). Furthermore, the connection weight method highlighted input variables’ distinct positive and negative impacts on permanent deformation.

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Mon Oct 16 2023
Journal Name
F1000research
Assessment of general population knowledge, attitude, and practice on safe unused and expired drugs disposal: a cross-sectional study
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Background The appropriate disposal of medication is a well-recognized issue that has convened growing recognition in several contexts. Insufficient awareness relating to appropriate methods for the disposal of unneeded medicine may result in notable consequences. The current research was conducted among the public in Iraq with the aim of examining their knowledge, attitude, and practices regarding the proper disposal of unused and expired medicines. Methods The present study used an observational cross-sectional design that was community-based. The data were obtained from using an online questionnaire. The study sample included people of diverse genders, regardless of their race or occupational status. The study mandated that all pa

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Publication Date
Thu Feb 06 2020
Journal Name
Scientific Reports
Waste foundry sand/MgFe-layered double hydroxides composite material for efficient removal of Congo red dye from aqueous solution
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Abstract<p>We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure</p> ... Show More
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Publication Date
Mon Oct 17 2016
Journal Name
Proceedings Of The Institution Of Mechanical Engineers, Part B: Journal Of Engineering Manufacture
Development and control of shaped metal deposition process using tungsten inert gas arc heat source in additive layered manufacturing
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Tungsten inert gas arc welding–based shaped metal deposition is a novel additive manufacturing technology which can be used for fabricating solid dense parts by melting a cold wire on a substrate in a layer-by-layer manner via continuous DC arc heat. The shaped metal deposition method would be an alternative way to traditional manufacturing methods, especially for complex featured and large-scale solid parts manufacturing, and it is particularly used for aerospace structural components, manufacturing, and repairing of die/molds and middle-sized dense parts. This article presents the designing, constructing, and controlling of an additive manufacturing system using tungsten inert gas plus wire–based shaped metal deposition metho

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Publication Date
Sun Dec 22 2024
Journal Name
Baghdad Science Journal
Thioflavin T Production in Coelastrella saipanensis LC752948.1: Impact of Sodium Chloride, growth phases, and their effect on growth parameters
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The present study aimed to investigate the possible production of Thioflavin T and the effect of NaCl concentrations and growth phases on the growth rate, doubling time and proline of C. saipanensis N. Hanagata (Scenedesmaceae, Shaerophleales). The alga was cultured in BG 11 medium and six NaCl concentrations were used in the experiments during different growth phases. The results have unveiled the presence of Triflavin T in the alga. The study results showed a growth rate decrease at all NaCl concentrations except in control treatment, while the doubling time, was recorded highest value (14 days) at the NaCl concentration of 0.08 M. The highest value of Proline (0.509 mg. Lˉ¹) was recorded at the treatment of 0.08 M of NaCl and recorded

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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Publication Date
Mon Sep 01 2025
Journal Name
Thermal Science And Engineering Progress
Active mixing strategies for energy-efficient water dispensers: Comparative experimental study of impeller and bubble injection in hot climates
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Publication Date
Fri Dec 01 2023
Journal Name
Materials Today Sustainability
Structure and performance of polyvinylchloride microfiltration membranes improved by green silicon oxide nanoparticles for oil-in-water emulsion separation
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Publication Date
Sat Nov 19 2022
Journal Name
Journal Of Solid State Electrochemistry
Thermal, electrical and electrochemical properties of ionic liquid-doped poly(ethylene oxide)–LiTDI polymer electrolytes for Li-ion batteries
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Publication Date
Mon Sep 02 2024
Journal Name
F1000research
Green synthesis of gold nanoparticles using Pelargonium Graveolens leaf extract: characterization and anti-microbial properties (An in-vitro study)
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Background In recent years, there has been a notable increase in the level of attention devoted to exploring capabilities of nanoparticles, specifically gold nanoparticles AuNPs, within context of modern times. AuNPs possess distinct biophysical properties, as a novel avenue as an antibacterial agent targeting Streptococcus Mutans and Candida Albicans. The aim of this study to create a nano-platform that has the potential to be environmentally sustainable, in addition to exhibiting exceptional antimicrobial properties against Streptococcus Mutans as well as Candida Albicans. Methods this study involved utilization of Pelargonium Graveolens leaves extract as a cost effective and environmentally sustainable app

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