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Introduction: Colposcopy is a medical procedure for detecting cervical lesions. Access to devices required for colposcopy procedures is limited in low- and middle-income countries. However, various existing digital imaging techniques based on artificial intelligence offer solutions to analyze colposcopy images and address accessibility challenges. Methods: We systematically searched PubMed, National Library of Medicine, and Crossref, which met our inclusion criteria for our study. Various methods and research gaps are addressed, including how variability in images and sample size affect the accuracy of the methods. The quality and risk of each study were assessed following the QUADAS-2 guidelines. Results: Development of image analysis and compression algorithms, and their efficiency are analyzed. Most of the studied algorithms have attained specificity, sensitivity, and accuracy which range from 86% to 95%, 75%–100%, and 100%, respectively, and these results were validated by the clinician to analyze the images quickly and thus minimize biases among the clinicians. Conclusion: This systematic review provides a comprehensive study on colposcopy image analysis stages and the advantages of utilizing digital imaging techniques to enhance image analysis and diagnostic procedures and ensure prompt consultations. Furthermore, compression techniques can be applied to send medical images over media for further analysis among periphery hospitals. [ABSTRACT FROM AUTHOR]

Malaria is an infectious disease caused by parasites of the genus Plasmodium spp. It is transmitted to humans by the bite of an infected female Anopheles mosquito. It is the most common disease in resource-poor settings, with 241 million malaria cases reported in 2020 according to the World Health Organization. Optical microscopy examination of blood smears is the gold standard technique for malaria diagnosis; however, it is a timeconsuming method and a well-trained microscopist is needed to perform the microbiological diagnosis. New techniques based on digital imaging analysis by deep learning and artificial intelligence methods are a challenging alternative tool for the diagnosis of infectious diseases. In particular, systems based on Convolutional Neural Networks for image detection of the malaria parasites emulate the microscopy visualization of an expert. Microscope automation provides a fast and low-cost diagnosis, requiring less supervision. Smartphones are a suitable option for microscopic diagnosis, allowing image capture and software identification of parasites. In addition, image analysis techniques could be a fast and optimal solution for the diagnosis of malaria, tuberculosis, or Neglected Tropical Diseases in endemic areas with low resources. The implementation of automated diagnosis by using smartphone applications and new digital imaging technologies in low-income areas is a challenge to achieve. Moreover, automating the movement of the microscope slide and image autofocusing of the samples by hardware implementation would systemize the procedure. These new diagnostic tools would join the global effort to fight against pandemic malaria and other infectious and poverty-related diseases. [ABSTRACT FROM AUTHOR]

Malaria is an infectious disease caused by parasites of the genus Plasmodium spp. It is transmitted to humans by the bite of an infected female Anopheles mosquito. It is the most common disease in resource-poor settings, with 241 million malaria cases reported in 2020 according to the World Health Organization. Optical microscopy examination of blood smears is the gold standard technique for malaria diagnosis; however, it is a time-consuming method and a well-trained microscopist is needed to perform the microbiological diagnosis. New techniques based on digital imaging analysis by deep learning and artificial intelligence methods are a challenging alternative tool for the diagnosis of infectious diseases. In particular, systems based on Convolutional Neural Networks for image detection of the malaria parasites emulate the microscopy visualization of an expert. Microscope automation provides a fast and low-cost diagnosis, requiring less supervision. Smartphones are a suitable option for microscopic diagnosis, allowing image capture and software identification of parasites. In addition, image analysis techniques could be a fast and optimal solution for the diagnosis of malaria, tuberculosis, or Neglected Tropical Diseases in endemic areas with low resources. The implementation of automated diagnosis by using smartphone applications and new digital imaging technologies in low-income areas is a challenge to achieve. Moreover, automating the movement of the microscope slide and image autofocusing of the samples by hardware implementation would systemize the procedure. These new diagnostic tools would join the global effort to fight against pandemic malaria and other infectious and poverty-related diseases.

In this study, wet air with ash particles was used to simulate real dryer exhaust from lignite-drying process, and its ash deposition characteristics along horizontal tube bundles were experimentally studied to provide theoretical guidance for the design and operation of waste heat recovery devices. The ash deposition on the longitudinal section of the tube bundles was considered, and the ash deposition thickness under different experimental conditions was quantitatively measured using digital imaging techniques. The spatial and temporal distributions of the ash deposition thickness and its variation with mainstream inlet temperature, mainstream velocity, water vapor mass fraction, and ash particle concentration were presented. The ash accumulated on the windward side of the tube bundles and mainly concentrated on the first five rows in the inlet section, especially on the first two rows. The rapid growth of ash deposition mainly occurred in the first 3000 s and then gradually stabilized. The ash deposition thickness was insensitive to the mainstream inlet temperature and velocity, whereas the water vapor mass fraction and ash particle concentration had significant influences on the ash deposition thickness. When the water vapor mass fraction increased from 5% to 15%, the average ash deposition thickness decreased from 7.67 mm to 1.87 mm. As the ash particle concentration increased from 1.0 g·m−3 to 14.8 g·m−3, the average ash deposition thickness increased from 1.91 mm to 26.0 mm. The change in ash deposition thickness was significantly larger than that in heat transfer coefficient under different conditions. [ABSTRACT FROM AUTHOR]

This paper aims to study the effects of spatial corrosion distribution and prestressing levels on the structural performance of corroded prestressed concrete (PC) beams via experimental studies. X-ray and digital image processing techniques are developed to visualize and quantify the spatial corrosion of strands in PC beams. The spatial characteristics of strand corrosion and its effect on the structural performance of PC beams are compared with those of reinforced concrete (RC) beams. Unlike RC beams showing more ductile behavior, the load-bearing capacity and ductility of the corroded PC beams are determined by the maximum local steel weight loss of an individual steel wire in the maximum bending moment region. The prestress force induces larger local maxima of steel corrosion and widens corrosion-induced cracks by elevating the concrete tensile strain in the transverse direction. • The effects of spatial corrosion and prestressing forces on the structural performance of PC beams are investigated. • Spatial corrosion of a strand and wires is quantified using X-ray and digital image processing techniques. • Higher prestressed force induces larger corrosion cracks and maximum steel weight loss. • Ductility and loading capacity of PC beams are more sensitive to corrosion than RC beams. • Spatial steel corrosion must be considered to evaluate the performance of corroded PC beams. [ABSTRACT FROM AUTHOR]

New scientific discoveries and directions have provided significant progress within the field of imaging technologies in recent years. One of the most important of these new scientific discoveries was the use of radiological imaging methods discovered in the late 19th and early 20th centuries in anthropological research. These methods enable the examination of both internal and external properties of an object by creating accurate virtual representations of the examined sample without destroying it. These developments in information technologies have created new research opportunities for anthropological studies and a new field called virtual anthropology has developed. Therefore, this article reviews the basic uses of various non-invasive imaging methods, such as conventional radiography, computed tomography, or micro-CT, as well as magnetic resonance imaging and ultrasound. The aim of this review is to discuss the benefit of using these imaging modalities for anthropological studies. [ABSTRACT FROM AUTHOR]

The combustion process in blast furnace (BF) has play a significant role in providing heat resources, reducing agent and primary gas flow distribution. Accordingly, large proportion energy was also consumed and discharging massive amount CO 2 , the most effective way to reduce that is to increase the pulverized coal injection (PCI) rate to substitute the coke and maintaining stability state of BF. But the relationship of PCI rate and raceway temperature is still unknown. In this paper, the temperature detection system based on digital imaging techniques (DIT) has been firstly applied to study the tuyere temperature regularity on various conditions in 2500 m3 BF, such as different PCI rates, PCI cease and none PCI processes. And the colorimetric method was used to calculate the temperature distributions of tuyere images in raceway zone of BF. Moreover, the calibration, denoising and edge detection were firstly used to improve the accuracy of temperature detection. At last the influence regularity of PCI rate on the tuyere temperature was obtained. The studies not only could contribute to qualify the effect of the PCI rate on the temperature distribution in raceway zone, but also could useful to understand the pulverized coal combustion mechanism in BF raceway zone. • Regularity of PCI rate on the Blast Furnace tuyere temperature was obtained. • Tuyere temperature changing regularity with and without PCI was studied. • Noise of Blast Furnace tuyere images was eliminated by the wavelet filter. • Edge of Blast Furnace tuyere images was detected by Morphological method. [ABSTRACT FROM AUTHOR]

As oriented strand board (OSB) increases in use, improving the mechanical properties is of importance. Improved in-plane shear properties will allow for more efficient use as well as open up other opportunities in engineered wood products with high shear stresses. Based on classical laminated plate theory, composite laminates with laminate alignment patterns produce higher in-plane shear modulus and strength compared with typical alignment. Oriented strand board was manufactured 13.3-mm thick with and alignment patterns, and in-plane shear, bending, nail connection, and small-scale shear wall properties compared to commercial OSB. Results showed a 24% increase in shear modulus for the alignment when compared with the alignment using a method similar to a standard in-plane shear test. Results also show 10% reduction in bending modulus of elasticity in the parallel direction. Small-scale shear wall tests were insensitive to changes of in-plane shear properties. Lateral nail connection tests showed no reduction in connection yield load, implying that these panels can be used in similar applications without affecting connection properties. [ABSTRACT FROM AUTHOR]

This paper presents the findings of an experimental research project that was conducted in two phases to study the behavior of glass fiber reinforced polymer (GFRP) sandwich panels with reinforced cores under in-plane loading conditions. The tested panels consisted of two GFRP face skins separated by a polymeric foam core. The foam core was reinforced with different configurations of through-thickness fiber insertions and through-thickness GFRP web skins. In the first phase the performance of three different types of structural connections was tested - namely, bolted, bonded, and so-called enhanced bolted connections. The findings indicate that bolted connections to thinner and more flexible panels exhibited lower strength and a higher degree of nonlinear behavior compared with the bonded connections to the same panels. In contrast, the bolted connections to thicker and stiffer panels were generally stronger and stiffer than their bonded counterparts. The findings further indicate that the ultimate strength of the connections can be increased by up to 26% by bonding a steel reinforcing plate to the face skins of the panel prior to bolting. In the second phase three full-scale sandwich panels (1400 mm × 1400 mm) with different panel configurations were tested under proportional, biaxial, in-plane loading. The applied loads were selected to simulate the in-plane loading conditions in sandwich panels that are subjected primarily to in-plane loads, such as webs of deep beams and shear walls in lightweight structures. The full-field strains and displacements of the panels were measured using a digital image correlation-based (DIC) non-contact measurement system. The findings indicate that the through-thickness core reinforcements effectively prevented localized buckling, debonding, and separation of the panels' face skins. The findings also demonstrated that slender panels exhibit shear-compression buckling failures, whereas less slender panels exhibit shear-tension rupture failures. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Image processing is an effective tool for automated monitoring of construction projects. For the last decade, it has gained increasing acceptance in its application to progress monitoring, productivity analyses, and quality assurance. However, a notable downside exists in image processing, especially in outdoor applications such as construction project monitoring: image quality is heavily affected by ambient lighting conditions. Poor or undesirable lighting conditions produce substandard quality images, which generally lead to a high level of errors in the related image processing for information extraction. This paper presents error-correction methods that can improve the image processing results for construction progress monitoring in the postprocessing stage. The methods are applied in the postprocessing stage. The key idea behind the error-correction methods is the concept of priority to classify input images and project information into several categories based on data reliability and intelligently use the classified information for more accurate analyses of the project progress. Tests in real construction sites showed that these postprocessing methods significantly increased the accuracy of image processing-based construction progress monitoring. [ABSTRACT FROM AUTHOR]

The integration of daylighting and electric lighting systems within buildings (also designated as 'green lighting') is a recent issue for the lighting research community: it allows achieving better lighting conditions for building occupants, in particular within office rooms. Besides the substitution of electric light, daylighting can contribute in a significant way to improve the users' visual comfort and performance, with a large variety of novel daylighting systems and components being developed in recent years. In order to demonstrate this, an anidolic daylighting system combined with several electric lighting fixtures was set up in an office room of the LESO solar experimental building located on the EPFL campus in Lausanne (Switzerland). Three different electric lighting modes,involving recessed luminaries (direct lighting), floor lamps (indirect lighting) and desk lamps (task lighting), were considered for that purpose. Luminance contrasts and glare indexes in the occupants' view field were monitored and compared in the officeroom, both in the presence and absence of daylight and for different sky conditions; the latter was achieved through luminance mappings based on high dynamic range imaging techniques. The energy performance of electric lighting systems was also considered, together with the qualitative aspect of lighting, in order to outline the main features that characterize an optimal integration of daylighting and electric lighting systems. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Ophthalmology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)