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.
In this paper, numerical and experimental studies on the elastic behavior of glass fiber reinforced polymer (GFRP) with stiffeners in the GFRP section's web (to prevent local buckling) are presented. The GFRP profiles were connected to the concrete deck slab by shear connectors. Two full-scale simply supported composite beams (with and without stiffeners) were tested under impact load (three-point load) to assess its structural response. The results proved that the maximum impact force, maximum deflection, damping time, and damping ratio of the composite beam were affected by the GFRP stiffeners. The experimental results indicated that the damping ratio and deflection were diminished compare
... Show MoreThe primary goal of root canal treatment (RCT) is to expel the presence of any necrotic or vital tissue, microbes and their byproducts from the canal space before press forward with the following steps of the RCT procedures. Although this is difficult to attain, various strives had been practiced by employing chemical and mechanical methods to eliminate as much microorganisms as possible and make the canal space valid for the obturation materials to be received. The aim of this review is to demonstrate some of what new remedies that could be used as root canal disinfectant by summarizing the recent studies regarding the efficacy of different natural products against the most persistence microbiota that could be responsible for most
... Show MoreThe novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic of coronavirus disease 2019 (COVID-19) which represents a global public health crisis. Based on recent published studies, this review discusses current evidence related to the transmission, clinical characteristics, diagnosis, management and prevention of COVID-19. It is hoped that this review article will provide a benefit for the public to well understand and deal with this new virus, and give a reference for future researches.
Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
... Show MoreSeeking pharmacist advice about minor ailments is a common practice among Iraqi patients because such advice is free and quick. Unfortunately, the assessment and management of minor ailments by Iraqi pharmacists were inappropriate. Therefore, this study aimed to develop a model for a mobile application that can assist community pharmacists in the diagnosis and management of minor ailments.
The scientific content of the application was based on the information in the symptoms in the pharmacy and British Nati
Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte
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