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A Past, Present, and Prospective Review on Microwave Nondestructive Evaluation of Composite Coatings
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Recent years have witnessed an increase in the use of composite coatings for numerous applications, including aerospace, aircraft, and maritime vessels. These materials owe this popularity surge to the superior strength, weight, stiffness, and electrical insulation they exhibit over conventional substances, such as metals. The growing demand for such materials is accompanied by the inevitable need for fast, accurate, and affordable nondestructive testing techniques to reveal any possible defects within the coatings or any defects under coating. However, typical nondestructive testing (NDT) techniques such as ultrasonic testing (UT), infrared thermography (IRT), eddy current testing (ECT), and laser shearography (LS) have failed to provide successful results when inspecting composite coatings. Consequently, microwave NDT techniques have emerged to compensate for the shortcomings of traditional NDT approaches. Numerous microwave NDT methods have been reported for composite coatings inspection. Although existing microwave NDT methods have shown successful inspection of composite coatings, they often face several challenges, such as low spatial image quality and extensive data interpretation. Nevertheless, many of these limitations can be addressed by utilizing microwave NDT techniques with modern technologies such as soft computing. Artificially intelligent techniques have greatly enhanced the reliability and accuracy of microwave NDT techniques. This paper reviews various traditional NDT techniques and their limitations in inspecting composite coatings. In addition, the article includes a detailed review of several microwave NDT techniques and their benefits in evaluating composite coatings. The paper also highlights the advantages of using the recently reported microwave NDT approaches employing artificial intelligence approaches. This review demonstrates that microwave NDT techniques in conjunction with artificial intelligence approaches have excellent prospects for further enhancing composite coatings inspection and assessment efficiency. The review aimed to provide the reader with a comprehensive overview of most NDT techniques used for composite materials alongside their most salient features.

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Publication Date
Mon Sep 04 2017
Journal Name
International Journal Of Environmental Science And Technology
A review of permeable reactive barrier as passive sustainable technology for groundwater remediation
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Publication Date
Thu Dec 01 2022
Journal Name
Environmental Nanotechnology, Monitoring & Management
Challenges in the implementation of bioremediation processes in petroleum-contaminated soils: A review
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Environmental pollution is regarded as a major problem, and traditional strategies such as chemical or physical remediation are not sufficient to overcome the problems of pollution. Petroleum-contaminated soil results in ecological problems, representing a danger to human health. Bioremediation has received remarkable attention, and it is a procedure that uses a biological agent to remove toxic waste from contaminated soil. This approach is easy to handle, inexpensive, and environmentally friendly; its results are highly satisfactory. Bioremediation is a biodegradation process in which the organic contaminants are completely mineralized to inorganic compounds, carbon dioxide, and water. This review discusses the bioremediation of petroleum-

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Publication Date
Sun Dec 10 2023
Journal Name
Journal Of Applied Engineering And Technological Science (jaets)
The Role of Artificial Intelligence in Diagnosing Heart Disease in Humans: A Review
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The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Ever

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Publication Date
Tue Feb 24 2015
Journal Name
Robotica
Multi-level control of zero-moment point-based humanoid biped robots: a review
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SUMMARY<p>Researchers dream of developing autonomous humanoid robots which behave/walk like a human being. Biped robots, although complex, have the greatest potential for use in human-centred environments such as the home or office. Studying biped robots is also important for understanding human locomotion and improving control strategies for prosthetic and orthotic limbs. Control systems of humans walking in cluttered environments are complex, however, and may involve multiple local controllers and commands from the cerebellum. Although biped robots have been of interest over the last four decades, no unified stability/balance criterion adopted for stabilization of miscellaneous walking/running modes of biped </p> ... Show More
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Publication Date
Thu Feb 13 2020
Journal Name
International Journal Of Environmental Research
Synthesis of a Novel Composite Sorbent Coated with Siderite Nanoparticles and its Application for Remediation of Water Contaminated with Congo Red Dye
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Abstract

Re-use of the byproduct wastes resulting from different municipal and industrial activities in the reclamation of contaminated water is real application for green projects and sustainability concepts. In this direction, the synthesis of composite sorbent from the mixing of waterworks and sewage sludge coated with new nanoparticles named “siderite” (WSSS) is the novelty of this study. These particles can be precipitated from the iron(II) nitrate using waterworks sludge as alkaline agent and source of carbonate. Characterization tests using X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) mapping revealed that the coating process was c

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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Finite Element Investigation on Shear Lag in Composite Concrete-Steel Beams with Web Openings
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In this paper, effective slab width for the composite beams is investigated with special emphasis on the effect of web openings. A three dimensional finite element analysis, by using finite element code ANSYS, is employed to investigate shear lag phenomenon and the resulting effective slab width adopted in the classical T-beam approach. According to case studies and comparison with limitations and rules stipulated by different standards and codes of practice it is found that web openings presence and panel proportion are the most critical factors affecting effective slab width, whereas concrete slab thickness and steel beam depth are less significant. The presence of web opening reduces effective slab width by about 21%.

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Publication Date
Tue Dec 19 2017
Journal Name
Al-khwarizmi Engineering Journal
Improve Wear Resistance on Al 332 Alloy Matrix- Micro -Nano Al2O3 Particles Reinforced Composite
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The wear behavior of alumina particulate reinforced A332 aluminium alloy composites produced by a stir casting process technique were investigated. A pin-on-disc type apparatus was employed for determining the sliding wear rate in composite samples at different grain size (1 µm, 12µm, 50 nm) and different weight percentage (0.05-0.1-0.5-1) wt% of alumina respectively. Mechanical properties characterization which strongly depends on microstructure properties of reinforcement revealed that the presence of ( nano , micro) alumina particulates lead to simultaneous increase in hardness, ultimate tensile stress (UTS), wear resistances. The results revealed that UTS, Hardness, Wear resistances increases with the increase in the percentage of

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Publication Date
Sun Mar 30 2025
Journal Name
Mustansiriyah Journal Of Pure And Applied Sciences
Secure E-voting authentication system employing biometric technology, Crypto-Watermarking Approach and blockchain technology: A Review
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Moderately, advanced national election technologies have improved political systems. As electronic voting (e-voting) systems advance, security threats like impersonation, ballot tampering, and result manipulation increase. These challenges are addressed through a review covering biometric authentication, watermarking, and blockchain technologies, each of which plays a crucial role in improving the security of e-voting systems. More precisely, the biometric authentication is being examined due to its ability in identify the voters and reducing the risks of impersonation. The study also explores the blockchain technology to decentralize the elections, enhance the transparency and ensure the prevention of any unauthorized alteration or

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Publication Date
Tue Oct 01 2024
Journal Name
Journal Of Engineering
A Comprehensive Review for Integrating Petrophysical Properties, Rock Typing, and Geological Modeling for Enhanced Reservoir Characterization
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Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

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