Search Results (1,421)

Mineralogy 4.0 can play a significant role in the future of geological research, education, and exploration by providing a more comprehensive and interactive understanding of rocks and minerals. This paper explores the application of digital photogrammetry and augmented reality (AR) technologies as part of Mineralogy 4.0. An atlas of 3D rocks and minerals with 915 high-quality models was created to showcase the potential of photogrammetry in the mineral sciences. The repository contains a wide range of sample types, featuring transparency, metallic luster, fluorescence, or millimetric-scale crystals. The three-dimensional rocks and minerals can also be accessed on-the-go through a mobile application that was developed for Android devices. Additionally, web applications have been developed with specific three-dimensional collections as well as three-dimensional storytelling. AR technology was also integrated into the 3D repository, allowing users to superimpose virtual 3D models of rocks and minerals onto real-world surfaces through their device’s camera. Also, a digital solution with 3D holograms of rocks and minerals was effectively implemented to provide an interactive and immersive experience. The 3D datasets of rocks and minerals can play a significant role in the geoscience community’s research, developing not only in-depth knowledge of specimens but also opening new frontiers in mineral sciences, leading towards a more advanced era of mineralogy. Full article

Steel structure flange connections are extensively employed in structural nodes due to their superior mechanical properties. This study combines fatigue testing and theoretical methods to investigate the fatigue performance of high-strength bolts in flange connections under actual gradient descent loads and provide fatigue design methods. Initially, fatigue tests were conducted on two sets of high-strength bolts under a gradient descent loading mode, yielding a total of 11 sets of fatigue data. Subsequently, the stress–life (S-N) curve was plotted using a cumulative damage model combined with an equivalent constant amplitude stress method, and the results were compared with existing fatigue design specifications. Additionally, digital cameras and electron microscopes were utilized to capture fatigue fracture images of the high-strength bolts, allowing a detailed investigation into the mechanisms underlying bolt fatigue fractures. The results indicate that the allowable stress amplitudes for the two sets of high-strength bolts, corresponding to a fatigue life threshold of 2 million cycles, were 144.211 MPa and 130.316 MPa, respectively—both of which exceed the values specified in current fatigue design codes. Moreover, finite element simulations revealed that the most pronounced stress concentration occurs at the first thread where the bolt and nut interface, which is identified as the critical location for fatigue fracture in bolts. The allowable stress and fatigue calculation method of bolts obtained in this study will provide a reference for flange node design Full article

The evaluation of smartphone camera technology for close-range photogrammetry includes assessing captured photos for 3D measurement. In this work, experiments are conducted on many smartphones to study distortion levels and accuracy performance in close-range photogrammetry applications. Analytical methods and specialized digital tools are employed to evaluate the results. OpenCV functions estimate the distortions introduced by the lens. Diagrams, evaluation images, statistical quantities, and indicators are utilized to compare the results among sensors. The accuracy achieved in photogrammetry is examined using the photogrammetric bundle adjustment in a real-world application. In the end, generalized conclusions are drawn regarding this technology’s use in close-range photogrammetry applications. Full article

This study deals with the color reproduction of a work of art to digitize it into a 3D realistic model. The experiment aims to digitize a work of art for application in a virtual reality environment concerning faithful color reproduction. Photogrammetry and scanning with a LiDAR sensor are used to compare the methods and work with colors during the reconstruction of the 3D model. An innovative tablet with a camera and LiDAR sensor is used for both methods. At the same time, current findings from the field of color vision and colorimetry are applied to 3D reconstruction. The experiment focuses on working with the RGB and L*a*b* color models and, simultaneously, on the sRGB, CIE XYZ, and Rec.2020(HDR) color spaces for transforming colors into a virtual environment. For this purpose, the color is defined in the Hex Color Value format. This experiment is a starting point for further research on color reproduction in the digital environment. This study represents a partial contribution to the much-discussed area of forgeries of works of art in current trends in forensics and forgery. Full article

Resin canals serve as a natural feature with the function of a defense system against fungi, bacteria, and insects. Trees can form these canals in response to mechanical injury and ecological disturbance. Factors, such as plant hormones and temperature, influence cambial activity and cell differentiation. This study examined the effects of increased temperature and plant hormones on cambial reactivation, vessel formation, and resin canal formation using localized heating and the application of the ethylene generator ethephon to dormant stems of the Toxicodendron vernicifluum seedlings. Localized heating was achieved by wrapping an electric heating ribbon around dormant stems, while ethephon was applied to the bark surface. Treatment was initiated on 29 January 2021, including control, heating, ethephon, and a combination of heating and ethephon. Cambial reactivation and resin canal formation were monitored using light microscopy, and bud growth was recorded with a digital camera. Localized heating induced earlier phloem reactivation, cambial reactivation, and xylem differentiation, increasing the number of vessels. The application of exogenous ethylene delayed these processes. The combination of localized heating and exogenous ethylene application resulted in smaller vessels and larger resin canals. These results suggest that increased temperature plays a significant role in cambial reactivation and vessel formation in ring-porous hardwood and that ethylene affects vessel differentiation and resin canal development. Full article

A simple and miniaturized protocol was developed for chloride extraction from Brazilian pre-salt crude oil for further salt determination by colorimetry. In this protocol, the colorimetric analysis of chloride using digital images was carried out in an aqueous phase obtained after a simple and miniaturized extraction carefully developed for this purpose. A portable device composed of a homemade 3D-printed chamber with a USB camera was used. The PhotoMetrix app converted the images into RGB histograms, and a partial least squares (PLS) model was obtained from chemometric treatment. The sample preparation was performed by extraction after defining the best conditions for the main parameters (e.g., extraction time, temperature, type and volume of solvent, and sample mass). The PLS model was evaluated considering the coefficient of determination (R²) and the root mean square errors (RMSEs)—calibration (RMSEC), cross-validation (RMSECV), and prediction (RMSEP). Under the optimized conditions, an extraction efficiency higher than 84% was achieved, and the limit of quantification was 1.6 mg g⁻¹. The chloride content obtained in the pre-salt crude oils ranged from 3 to 15 mg g⁻¹, and no differences (ANOVA, 95%) were observed between the results and the reference values by direct solid sampling elemental analysis (DSS-EA) or the ASTM D 6470 standard method. The easy-to-use colorimetric analysis combined with the extraction method’s simplicity offered a high-throughput, low-cost, and environmentally friendly method, with the possibility of portability. Additionally, the decrease in energy consumption and waste generation, increasing the sample throughput and operators’ safety, makes the proposed method a greener approach. Furthermore, the cost savings make this a suitable option for routine quality control, which can be attractive in the crude oil industry. Full article

The optical remote sensors carried by the Jilin-1 KF02 series satellites have an imaging resolution better than 0.5 m and a width of 150 km. There are radiometric problems, such as stripe noise, vignetting, and inter-slice chromatic aberration, in their raw images. In this paper, a relative radiometric correction method based on temperature normalization is proposed for the response characteristics of sensors and the structural characteristics of optical splicing of Jilin-1 KF02 series satellites cameras. Firstly, a model of temperature effect on sensor output is established to correct the variation of sensor response output digital number (DN) caused by temperature variation during imaging process, and the image is normalized to a uniform temperature reference. Then, the horizontal stripe noise of the image is eliminated by using the sensor scan line and dark pixel information, and the vertical stripe noise of the image is eliminated by using the method of on-orbit histogram statistics. Finally, the method of superposition compensation is used to correct the vignetting area at the edge of the image due to the lack of energy information received by the sensor so as to ensure the consistency of the image in color and image quality. The proposed method is verified by Jilin-1 KF02A on-orbit images. Experimental results show that the image response is uniform, the color is consistent, the average Streak Metrics (SM) is better than 0.1%, Root-Mean-Square Deviation of the Mean Line (RA) and Generalized Noise (GN) are better than 2%, Relative Average Spectral Error (RASE) and Relative Average Spectral Error (ERGAS) are greatly improved, which are better than 5% and 13, respectively, and the relative radiation quality is obviously improved after relative radiation correction. Full article

Astrogeodetic deflections of the vertical (DoVs) are close indicators of the slope of the geoid. Thus, DoVs observed along horizontal profiles may be integrated to create geoid undulation profiles. In this study, we collected DoV data in the Eastern Swiss Alps using a Swiss Digital Zenith Camera, the COmpact DIgital Astrometric Camera (CODIAC), and two total station-based QDaedalus systems. In the mountainous terrain of the Eastern Swiss Alps, the geoid profile was established at 15 benchmarks over a two-week period in June 2021. The elevation along the profile ranges from 1185 to 1800 m, with benchmark spacing ranging from 0.55 km to 2.10 km. The DoV, gravity, GNSS, and levelling measurements were conducted on these 15 benchmarks. The collected gravity data were primarily used for corrections of the DoV-based geoid profiles, accounting for variations in station height and the geoid-quasigeoid separation. The GNSS/levelling and DoV data were both used to compute geoid heights. These geoid heights are compared with the Swiss Geoid Model 2004 (CHGeo2004) and two global gravity field models (EGM2008 and XGM2019e). Our study demonstrates that absolute geoid heights derived from GNSS/leveling data achieve centimeter-level accuracy, underscoring the precision of this method. Comparisons with CHGeo2004 predictions reveal a strong correlation, closely aligning with both GNSS/leveling and DoV-derived results. Additionally, the differential geoid height analysis highlights localized variations in the geoid surface, further validating the robustness of CHGeo2004 in capturing fine-scale geoid heights. These findings confirm the reliability of both absolute and differential geoid height calculations for precise geoid modeling in complex mountainous terrains. Full article

Recently, as the types of imported food and the design of their packaging become more complex and diverse, digital recognition technologies such as barcodes, QR (quick response) codes, and OCR (optical character recognition) are attracting attention in order to quickly and easily check safety information (e.g., food ingredient information and recalls). However, consumers are still exposed to inaccurate and inconvenient situations because legacy technologies require dedicated terminals or include information other than safety information. In this paper, we propose a deep learning-based packaging recognition system which can easily and accurately determine food safety information with a single image captured through a smartphone camera. The detection algorithm learned a total of 100 kinds of product images and optimized YOLOv7 to secure an accuracy of over 95%. In addition, a new SUS (system usability scale)-based questionnaire was designed and conducted on 71 consumers to evaluate the usability of the system from the individual consumer’s perspective. The questionnaire consisted of three categories, namely convenience, accuracy, and usefulness, and each received a score of at least 77, which confirms that the proposed system has excellent overall usability. Moreover, in terms of task completion rate and task completion time, the proposed system is superior when it compared to existing QR code- or Internet-based recognition systems. These results demonstrate that the proposed system provides consumers with more convenient and accurate information while also confirming the sustainability of smart food consumption. Full article

Replacing mechanical utility meters with digital ones is crucial due to the numerous benefits they offer, including increased time resolution in measuring consumption, remote monitoring capabilities for operational efficiency, real-time data for informed decision-making, support for time-of-use billing, and integration with smart grids, leading to enhanced customer service, reduced energy waste, and progress towards environmental sustainability goals. However, the cost associated with replacing mechanical meters with their digital counterparts is a key factor contributing to the relatively slow roll-out of such devices. In this paper, we present a low-cost and power-efficient solution for retrofitting the existing metering infrastructure, based on state-of-the-art communication and artificial intelligence technologies. The edge device we developed contains a camera for capturing images of a dial meter, a 32-bit microcontroller capable of running the digit recognition algorithm, and an NB-IoT module with (E)GPRS fallback, which enables nearly ubiquitous connectivity even in difficult radio conditions. Our digit recognition methodology, based on the on-device training and inference, augmented with federated learning, achieves a high level of accuracy (97.01%) while minimizing the energy consumption and associated communication overhead (87 $\mathsf{\mu }$Wh per day on average). Full article

Luminance is the fundamental photometric quantity representing the technical meaning of brightness. It is usually measured from a distance using a matrix sensor, which is the basis of the professional instrument. However, specific technical requirements must be fulfilled to achieve accurate results. This paper considers whether modern high-resolution smartphone cameras are suitable for luminance measurements. Three cameras from high-end smartphones were evaluated on a dedicated laboratory stand. The sensors’ output characteristics showed relatively good linearity of the individual R, G, and B channels. Unfortunately, the spectral sensitivities were unfavorable, as the minimum error achieved was about 17%. This device is classified outside the generally accepted quality scale for photometric instruments. The presented investigation confirmed that none of the high-resolution smartphone cameras tested was suitable for use as a universal luminance camera. However, one of the test devices can be developmental if restrictively calibrated and used only in a specialistic laboratory stand. Using a smartphone (or only its camera) for luminance measurements requires proper advanced calibration. It is possible, but it limits us to only dedicated applications. The pilot study presented in this paper will help create a suitable test stand for spectacle vision systems, e.g., virtual reality equipment. Full article

Estimating canopy volumes of strawberry plants can be useful for predicting yields and establishing advanced management plans. Therefore, this study evaluated the spatial variability of strawberry canopy volumes using a ResNet50V2-based convolutional neural network (CNN) model trained with RGB images acquired through manual unmanned aerial vehicle (UAV) flights equipped with a digital color camera. A preprocessing method based on the You Only Look Once v8 Nano (YOLOv8n) object detection model was applied to correct image distortions influenced by fluctuating flight altitude under a manual maneuver. The CNN model was trained using actual canopy volumes measured using a cylindrical case and small expanded polystyrene (EPS) balls to account for internal plant spaces. Estimated canopy volumes using the CNN with flight altitude compensation closely matched the canopy volumes measured with EPS balls (nearly 1:1 relationship). The model achieved a slope, coefficient of determination (R²), and root mean squared error (RMSE) of 0.98, 0.98, and 74.3 cm³, respectively, corresponding to an 84% improvement over the conventional paraboloid shape approximation. In the application tests, the canopy volume map of the entire strawberry field was generated, highlighting the spatial variability of the plant’s canopy volumes, which is crucial for implementing site-specific management of strawberry crops. Full article

This paper mainly studies the fatigue cracks growth of fillet weld specimens in a fashion that is consistent with that used to assess the fatigue performance of complex aerospace structures under operational flight loads. The fatigue test loads were determined using the overall finite element analysis results of the hopper wagon. The actual applied test loads were monitored using strain gauges. The residual stress in the critical region was determined by combining the stress field of the welded specimen obtained by a thermal imager under cyclic loading with the results of the three-dimensional finite element analysis of the specimen. During the fatigue test, a digital camera (with microscope lens) was used in conjunction with infrared measurement technology to obtain the crack growth information. As in prior studies, the three dimensional finite element alternating technique was used to calculate the stress intensity factor in the critical area of the crack in the fillet weld specimen. The Hartman–Schijve crack growth equation was then used, in conjunction with the calculated stress intensity factor solutions, to compute the crack growth history in a fatigue test of a critical welded component in a hopper wagon. The resultant computed crack growth histories are relatively consistent with the test results. Full article

Cellular materials such as aluminum and polyurethane foams are recognized for their effectiveness in energy absorption. They commonly serve as crushable cores in sacrificial cladding for blast mitigation purposes. This study delves into the effectiveness of autoclaved aerated concrete (AAC), a lightweight, porous material known for its energy-absorbing properties as a crushable core in sacrificial cladding. The experimental set-up features a rigid frame made of steel measuring 1000 × 1000 × 15 mm³ with a central square opening (300 × 300 mm²) holding a 2 mm thick aluminum plate representing the structure. The dynamic response of the aluminum plate is captured using two high-speed cameras arranged in a stereoscopic configuration. Three-dimensional digital image correlation is used to compute the transient deformation fields. Blast loading is achieved by detonating 20 g of C4 explosive set at 250 mm from the plate’s center. The study assesses the mineral foam’s absorption capacity by comparing out-of-plane displacement and mean permanent deformation of the aluminum plate with and without the protective solution. Six foam configurations (A to F) are tested experimentally and numerically, varying in the foam’s free space for expansion relative to its total volume. Results show positive protective effects, with configuration F reducing maximum deflection by at least 30% and configuration C by up to 70%. Foam configuration influences energy dissipation, with an optimal lateral surface-to-volume ratio (ζ) enhancing protective effects, although excessive ζ leads to non-uniform foam crushing. To address the influence of front skin deformability, a non-deformable front skin has been adopted. The latter demonstrates an increased effectiveness of the sacrificial cladding, particularly for ζ values above the optimal value obtained when using a deformable front skin. Notably, using a non-deformable front skin increases maximum deflection reduction and foam energy absorption by up to approximately 30%. Full article

Background: The gold standard for crystal arthritis diagnosis relies on the identification of either monosodium urate (MSU) or calcium pyrophosphate (CPP) crystals in synovial fluid. With the goal of enhanced crystal detection, we adapted a standard compensated polarized light microscope (CPLM) with a polarized digital camera and multi-focal depth imaging capabilities to create digital images from synovial fluid mounted on microscope slides. Using this single-shot computational polarized light microscopy (SCPLM) method, we compared rates of crystal detection and raters’ preference for image. Methods: Microscope slides from patients with either CPP, MSU, or no crystals in synovial fluid were acquired using CPLM and SCPLM methodologies. Detection rate, sensitivity, and specificity were evaluated by presenting expert crystal raters with (randomly sorted) CPLM and SCPLM digital images, from FOV above clinical samples. For each FOV and each method, each rater was asked to identify crystal suspects and their level of certainty for each crystal suspect and crystal type (MSU vs. CPP). Results: For the 283 crystal suspects evaluated, SCPLM resulted in higher crystal detection rates than did CPLM, for both CPP (51%. vs. 28%) and MSU (78% vs. 46%) crystals. Similarly, sensitivity was greater for SCPLM for CPP (0.63 vs. 0.35) and MSU (0.88 vs. 0.52) without giving up much specificity resulting in higher AUC. Conclusions: Subjective and objective measures of greater detection and higher certainty were observed for SCPLM over CPLM, particularly for CPP crystals. The digital data associated with these images can ultimately be incorporated into an automated crystal detection system that provides a quantitative report on crystal count, size, and morphology. Full article