Search Results (179)

Background/Objectives: Limited research has evaluated the association between the triglyceride-to-high-density lipoprotein (TG/HDL) ratio and premature coronary artery disease (PCAD), particularly in Saudi Arabia. Therefore, this study aimed to investigate the association of the TG/HDL ratio with PCAD and to assess its sensitivity and specificity in a young Saudi population. Methods: This comparative retrospective case–control study utilized data collected from patients’ electronic medical records at King Saud University Medical City (KSUMC) between 2015 and 2023. The vessel score and Gensini score were used to evaluate the severity of coronary occlusion. The study population was divided into two groups: (1) a healthy control group consisting of blood bank donors, selected to exclude individuals with chronic diseases such as metabolic disorders and hypertension, with no evidence of coronary artery disease and aged ≤50 years (as confirmed by a cardiologist to rule out cardiovascular disease); and (2) patients with PCAD, aged ≤51 years, who underwent selective coronary angiography using the standard hospital procedure (right femoral artery approach). Coronary angiographic images were evaluated using right and left oblique views with cranial and caudal angulations. Results: A total of 898 subjects were included in the study, comprising 440 healthy controls and 458 patients with PCAD. Higher HbA1c levels were significantly associated with PCAD (adjusted OR = 13.03, 95% CI [7.32, 23.18], p < 0.001). Importantly, the TG/HDL ratio, the primary biomarker of interest, remained significantly associated with PCAD after full adjustment. Each unit increase in the TG/HDL ratio was associated with more than a threefold increase in the odds of PCAD (adjusted OR = 3.39, 95% CI [2.22, 5.16], p < 0.001), independent of age, sex, BMI, HbA1c, smoking, and total cholesterol levels. Among females, the TG/HDL ratio demonstrated an area under the curve (AUC) of 0.796, with an optimal cut-off value of 0.91, yielding 77.8% sensitivity and 71.4% specificity. Among males, the TG/HDL ratio yielded an AUC of 0.786, with a higher optimal cut-off value of 1.09 providing 73.4% sensitivity and 65.4% specificity. Conclusions: Our study indicates that the TG/HDL ratio and HbA1c are significantly associated with PCAD in young Saudi male and female populations, demonstrating good sensitivity and specificity. Females exhibited a lower cut-off value than males. Smoking and elevated cholesterol levels were also identified as prominent risk factors. However, the TG/HDL ratio did not distinguish between moderate and severe coronary stenosis, as assessed by the Gensini score. Full article

We propose KoSim-GL, a large-scale vision-based geo-localization dataset for drone positioning in GPS-denied environments. Geo-localization estimates a drone’s location by matching drone-view imagery against a geo-referenced satellite image database, offering a reliable alternative to GPS under conditions such as signal jamming, spoofing, or degradation in dense urban canyons. Although this task is challenging due to the domain gap between drone-view and satellite-view imagery, existing benchmarks are built predominantly around urban environments in the United States and China, leaving South Korea largely unrepresented, despite its distinctive landscape in which mountainous terrain coexists with dense high-rise districts and low-rise residential neighborhoods. To address this gap, we introduce KoSim-GL, constructed from drone-view images captured via an AirSim- and ROS-based flight simulator and satellite images collected through the Google Maps Tile API, covering the urban area of Daejeon, South Korea. Its key feature is a multi-view configuration that simultaneously captures five views, one nadir and four oblique, at each flight position across altitudes from 100 m to 600 m, enabling robust localization even in feature-sparse environments where nadir-only matching is prone to fail. In total, KoSim-GL comprises 2,450,315 drone images and 1704 satellite images. We further provide systematic comparisons against five existing benchmarks and baseline evaluations of ten representative geo-localization models under single- and multi-view settings. Experimental results show that the multi-view configuration substantially improves localization performance; for example, FSRA improves Recall@1 from 44.08% (single-view) to 65.37% (multi-view), a gain of 21.29 percentage points. The dataset is publicly available. Full article

Accurate crack width measurement is important for structural condition assessment, but image-based methods are sensitive to oblique viewing angles and varying imaging distances. To address this challenge, this study proposes a method and evaluation framework for crack width measurement under non-orthogonal imaging conditions using RGB-D sensors. The proposed method integrates plane fitting and homography-based geometric rectification to transform imaged cracks into standard orthogonal viewpoints. It then applies dynamic masking and hybrid global–local binarization to the rectified image to improve measurement accuracy and robustness. Finally, this study develops an evaluation framework for comparing the proposed and baseline methods under different viewing angles and imaging distances. The framework establishes correspondences between physical locations along the same crack across RGB-D images captured under different imaging conditions, enabling quantitative analysis of performance variations. Experiments on two cracks in concrete buildings show that the proposed method outperforms the baseline method without geometric rectification, reducing the fitted surface error by 19.3–52.3% while maintaining a validity rate above 99%. The results indicate that incorporating surface geometry offers a practical pathway for quantitative crack assessment in close-range image-based inspection using handheld or UAV-mounted RGB-D cameras. Full article

Detecting hail from remote sensing observations remains challenging because hail develops rapidly and its signatures may appear at different levels within a storm. Ground-based radar and geostationary meteorological satellites are the two primary observing systems for this task, yet their observations are often spatially misaligned. Satellite measurements mainly characterize the thermal structure near the cloud top, whereas radar observations capture the lower-level precipitation core. This mismatch is further exacerbated by satellite parallax, namely the apparent horizontal shift of high cloud tops caused by the oblique viewing geometry of a geostationary satellite, together with the vertical tilt of convective storms. Existing joint methods generally combine satellite cloud-top information with radar precipitation information directly, without explicitly correcting the spatial displacement, which limits detection accuracy. To address this issue, we propose HailDeformer, a deep learning framework that first aligns satellite and radar features through a bidirectional deformable cross-attention module equipped with a position-wise confidence gate and optimized with smoothness, contrastive alignment, and observation-structure consistency losses, and then refines the fused representation using an inter-scale attention module and a wavelet-guided refinement module. Experiments on a four-region dataset from China show that HailDeformer consistently outperforms Direct Fusion, Manual Weighting, Cross-Attention Fusion, and Optical Flow Alignment, achieving a mean Average Precision at IoU 0.5 (mAP@0.5) of 0.916, an F1 score of 0.864, a Critical Success Index (CSI) of 0.760, and the lowest False Alarm Ratio (FAR) of 0.149. Ablation studies further confirm that all proposed modules and associated constraints contribute to the overall performance, with the alignment module providing the largest improvement. Additional evaluations demonstrate that HailDeformer remains effective throughout storm evolution and under challenging observational conditions. Full article

Existing self-supervised methods have achieved significant success in ground-level autonomous driving scenarios, but applying them directly to Unmanned Aerial Vehicle (UAV) videos remains challenging. On the one hand, rapid pose changes in UAVs often lead to oblique-view imaging, making it difficult for conventional methods to handle the perspective distortion in oblique imagery. On the other hand, complex UAV viewpoints may cause depth blurring in low-texture regions. To address these challenges, we propose a lightweight self-supervised monocular depth estimation method for UAV scenarios. By utilizing a Dynamic Direction-Aware Module (DDaM), the network adaptively adjusts the sampling grid to correct distorted features during feature extraction, while enhancing its ability to capture features at different spatial locations. Furthermore, to mitigate the loss of spatial information caused by multiple downsampling operations, we integrate a Coordinate Attention Mechanism into the encoder. This mechanism captures features along two separate spatial axes, preserving the spatial coordinates of object boundaries. Our experiments demonstrate that the synergy between DDaM and the Coordinate Attention Mechanism enables the prediction of more accurate object boundaries and richer local details. To validate the effectiveness and practical applicability of the proposed method, we conduct experiments on both the MidAir synthetic dataset and the UAVid real-world dataset. The results show that, compared with current baseline methods, our approach maintains competitive performance while requiring the fewest parameters. Full article

Rapid detection of wilt-affected pine crowns in mountainous forests is hindered by occlusion, self-shadowing, and heterogeneous backgrounds in conventional nadir products. We evaluated whether oblique UAV RGB imagery improves crown-level detection relative to nadir imagery under matched site, season, sensor, and workflow conditions. The workflow was designed for rapid post-flight screening of geotagged UAV photographs. Paired nadir orthophotos and 45–70° oblique photographs were acquired over pine stands in Wenshan Prefecture, Yunnan, China, and organized into D1 (nadir), D2 (oblique), and D3 (simple mixed-view concatenation). Three YOLO11 detectors were trained for crown shoot damage ratio (SDR)-derived operational classes: early-stage (SDR < 50%), severely damaged (SDR ≥ 50%), and withered (needle-free dead crowns). A paired crown-level RGB subset (n = 20 crowns observed in both views) was analyzed as supporting evidence for view-dependent appearance differences. The oblique-image model (D2) achieved the highest validation performance, with precision of 0.994, recall of 0.991, F1-score of 0.989, mAP@0.5 of 0.995, and mAP@0.5:0.95 of 0.880. The paired subset showed a significant multivariate RGB profile difference between views (Hotelling’s T2 = 58.91, F = 3.10, p = 0.044), driven mainly by reduced Excess Green and greater dispersion of blue-related traits under oblique viewing. These results indicate that oblique UAV photographs retain additional crown-edge, lateral-structure, and chromatic context for detecting wilt-affected pine crowns. Oblique RGB imagery therefore provides a practical, low-cost input for rapid forest health surveillance and targeted field verification in rugged pine landscapes. Full article

Background: Cage subsidence (CS) is among the main complications after oblique lumbar interbody fusion (OLIF) and may lead to the failure of indirect decompression. Accurate preoperative bone quality assessment is critical for risk stratification, yet the optimal imaging modality and diagnostic threshold remain unclear. Objectives: This study aimed to determine a quantitative computed tomography (QCT)-derived volumetric bone mineral density (vBMD) threshold for predicting CS after OLIF with posterior fixation. Methods: Patients undergoing OLIF with posterior fixation between July 2017 and March 2020 were retrospectively enrolled. Preoperative vBMD was measured using QCT as the average L2–L4 trabecular volumetric BMD. CS was defined as a loss of more than 2 mm of disk height on sagittal midline CT views between 3 days postoperatively and the last follow-up. Clinical and radiographic parameters including gender, age, body mass index, vBMD, number of operative levels, cage dimensions, disk height, segmental lordosis, intraoperative endplate injury, and fusion status were analyzed. Results: 86 patients (107 operative levels) with a mean follow-up of 20.6 months were included; 25 levels (23.4%) developed CS. Multivariate logistic regression identified vBMD (p < 0.001; OR 0.947; 95% CI 0.923–0.972) and intraoperative endplate injury (p = 0.031; OR 3.640; 95% CI 1.125–11.776) as independent risk factors. The area under the receiver operating characteristic curve (AUC) for vBMD was 0.847 (95% CI, 0.762–0.932), with an optimal threshold of 83.0 mg/cm³ (sensitivity 84.0%, specificity 76.8%). This threshold closely aligns with the American College of Radiology QCT criterion for osteoporosis (80 mg/cm³); however, given that it was derived from a single-center retrospective cohort, external validation in multi-center studies is warranted before broad clinical adoption. Fusion rates differed significantly between CS and non-CS groups (84.0% vs. 96.3%, p = 0.029). Conclusions: QCT-derived vBMD provides a phantom-calibrated, protocol-standardized metric for preoperative risk stratification of cage subsidence after OLIF. Full article

An AI video–based assessment system is used to analyze the volleyball forearm pass under continuous wall-volley conditions in this study. A single 120 frames per second (FPS) high-speed camera captures the athlete from a rear-oblique view. A laptop executes a You Only Look Once (YOLO)-based pipeline to detect the ball and human keypoints, including the shoulders, elbows, wrists, hips, knees, and ankles. From the joint angles and ball–body relative positions, three cues are quantified. The first cue is the ready posture, characterized by straight arms, downward wrist flexion, an upper arm–trunk angle of approximately 90°, and a forward-leaning center of mass. The second cue is the ball–contact point located posterior to the wrist joint. The third cue is the variation in the center of mass synchronized with the rhythm of the ball. Five athletes performed ten trials, and the predictions were compared against manual annotations, achieving greater than 95% accuracy in criterion attainment. The system outputs criterion scores and key frames to provide immediate feedback. Deployment challenges, including occlusion, viewpoint, and illumination, are discussed, along with potential extensions such as multi-camera fusion and temporal tracking. Full article

For power-grid applications such as transmission corridor inspection, substation asset inspection, and post-disaster emergency repair, reliable UAV self-localization under GNSS-degraded or GNSS-denied conditions is critical to ensuring operational safety and accurate defect geotagging. Due to substantial discrepancies in viewpoint, scale, and geometric structure between oblique UAV images and nadir satellite images, conventional RGB-based cross-view retrieval methods often suffer from unstable alignment and insufficient geometric modeling, particularly in scenarios with repetitive textures and partial overlap. To address these challenges, we propose a cross-view visual geo-localization model that integrates RGBD multimodal inputs with multi-scale attention enhancement. Specifically, MiDaS is used to estimate relative depth from UAV imagery, which is concatenated with RGB to form a four-channel input, while satellite images are padded with an additional zero channel to maintain dimensional consistency. A shared-weight ViTAdapter is adopted to learn joint semantic–geometric representations, and a lightweight Efficient Multi-scale Attention (EMA) module is adopted on spatial feature maps to strengthen multi-scale spatial consistency. In addition, an IoU-weighted InfoNCE loss is employed to accommodate partial matching during training, thereby improving the robustness of feature alignment. Experiments on the GTA-UAV dataset under the cross-area protocol show stable performance across both retrieval and localization metrics. Specifically, Recall@1, Recall@5, and Recall@10 reach 18.12%, 38.83%, and 49.47%, respectively; AP is 28.01 and SDM@3 is 0.53; meanwhile, the top-1 geodesic distance error Dis@1 is 1052.73 m. These results indicate that explicit geometric priors combined with multi-scale spatial enhancement can effectively improve cross-view feature alignment, leading to enhanced robustness and accuracy for localization in challenging power inspection scenarios. Full article

In a perspective projection, a circular target appears as an ellipse for an oblique view. Herein, the ellipse center obtained from image coordinate measurement operators differs from the projection of the circle center. This discrepancy is called eccentricity and may lead to systematic errors. This article documents the significance of these discrepancies and discusses five different correction methods that can be applied in the image space or as a model adaptation. Two of the methods include the determination of the circle radius and thus also offer a possibility to define the scale. The eccentricity correction procedures are validated in a series of experiments, which proved that even extreme eccentricity effects can be fully compensated. In the experiment on the approaches including scale determination, the precision and accuracy of the scale definition is investigated, obtaining relative accuracies of 0.5–1%. Full article

In contemporary museum design, architects increasingly treat spatial experience as a medium of visitor engagement, yet movement is often reduced to a problem of routing and orientation rather than recognised as engagement in its own right. This study shows how Steven Holl’s parallax operates as a motivational mechanism at the Kiasma Museum of Contemporary Art. Parallax, a phenomenological and ecological construct, is examined through oblique thresholds, overlapping perspectives, and layered illumination. Integrating phenomenology, ecological psychology, and spatial configuration analysis, this study links embodied perception to measurable spatial properties. Spatial relations were quantified using space syntax—axial line analysis, justified graphs, and isovist analysis—alongside luminance and visual saliency mapping of Kiasma’s second and third floors. The results reveal a dominant ring structure in which visibility tightens at thresholds and views shift continuously along the route. Pronounced brightness gradients accompany these transitions and intensify perceived change along the sequence. These coupled spatial and luminous strategies may encourage exploratory navigation, positioning wayfinding as integral to the museum experience. This study argues that parallax links spatial configuration to embodied engagement, emerging as a perceptual effect produced through the interaction of spatial layout, luminous modulation, and bodily movement rather than functioning as a fixed design principle. Full article

Long-wave infrared (LWIR) airborne optical systems for ground imaging are widely utilized in applications such as ground reconnaissance, agricultural monitoring, counterterrorism, and other fields. Traditional oblique-view ground-imaging optical systems suffer from a critical drawback compared to nadir-view systems: the significant variation in object distances between distant and nearby targets. This disparity leads to inconsistent ground resolution (GR), manifesting in images where distant targets exhibit significantly lower resolution than nearby ones. This characteristic is highly detrimental to information acquisition and three-dimensional modeling of the system. Furthermore, the limited field of view of fixed focal length systems prevents the unmanned aerial vehicle (UAV) from acquiring target information effectively across varying flight altitudes. To address this issue, this paper designs an oblique imaging optical system capable of achieving both constant GR and zoom functionality in the LWIR band. By controlling the ground resolution, a LWIR continuous zoom optical system was designed. The system maintains constant GR over the entire field of view. Its modulation transfer function (MTF) approaches the diffraction limit across the full field of view, and the spot diagram remains within Airy’s disk at each view angle. The radius of the spot diagram is smaller than that of the Airy disk, indicating that the geometric aberrations of the system are well corrected. The imaging performance is primarily determined by the wavelength and the F-number. In the case of LWIR, the longer wavelength results in a larger Airy disk radius. The system meets imaging quality requirements and is suitable for air-to-ground target reconnaissance imaging. Full article

Taking the Daliang Tunnel of the Lanzhou–Xinjiang High-speed Railway crossing a reverse strike-slip fault as the engineering background, seismic damage investigations of the Daliang Tunnel and other cross-fault tunnels under earthquake action were conducted. Using 1:50 meso-scale model tests, experimental analyses were carried out on the lining strain response, internal crack development and failure, and surrounding rock pressure variation during fault dislocation. The failure modes and mechanisms of tunnels crossing reverse strike-slip faults were thoroughly explored. Meanwhile, a three-dimensional numerical model of the Daliang Tunnel was established to investigate the influence of dislocation modes with structural zonation within the fault zone on the surrounding rock response. The results indicate that the damage and strain response of the tunnel lining are mainly distributed within the fracture zone, predominantly characterized by combined oblique shear and compression failure. Due to the displacement of the lining induced by strong surrounding rock movement, surrounding rock pressure exhibits considerable variation at the boundaries of the fracture zone, accompanied by certain void detachment phenomena. The overall deformation of the tunnel crossing the reverse strike-slip fault presents an “S”-shaped pattern, which is consistent with the numerical simulations. The compression and dislocation morphology of the sidewalls within the rupture surface is in good agreement with the point cloud plan view. The compressive deformation and strain of the surrounding rock are most significant within the rupture surface. Meanwhile, the soft-to-hard transition segments between the new fracture zone and the rupture surface, as well as between the rupture surface and the influence zone, exhibit a trend of first decreasing and then increasing. Full article

Accurate target localization via matching real-time UAV images with reference satellite imagery is essential for autonomous environmental perception. Nonetheless, operational constraints and weather conditions often necessitate oblique photography. This large-tilt mode causes significant perspective and radiometric distortions, resulting in a substantial domain gap between UAV and vertical satellite imagery. The scarcity of datasets featuring extreme viewpoint shifts and fine-grained ground-truth labels hinders the validation of image matching algorithms in multi-tilt-angle environments. To address this issue, we introduce the multiple-tilt-angle dataset (MTA-Dataset), containing 1892 UAV images with tilt angles spanning $\left[0°,\right.\left.90°\right)$ and flight altitudes up to 300 m, supported by high-precision five-point manual annotations. Based on this benchmark, we evaluate state-of-the-art matching algorithms and propose a spatial-resolution-based cropping strategy. Experimental results demonstrate that, as the UAV tilt angle increases within the range of $\left[0°,\right.\left.90°\right)$, although the expanding field of view provides richer contextual information, the localization errors of all methods increase significantly and matching precision drops sharply due to severe geometric distortions in far-field regions and interference from redundant background information, with performance deteriorating most drastically in the $\left[50°,\right.\left.90°\right)$ range. With the integration of our strategy, the average matching localization errors of SuperPoint + SuperGlue baseline for UAV images within the tilt-angle ranges of $\left[50°,\right.\left.60°\right)$, $\left[60°,\right.\left.70°\right)$, $\left[70°,\right.\left.80°\right)$, and $\left[80°,\right.\left.90°\right)$ are reduced by 33.49 m, 37.86 m, 98.3 m, and 109.95 m, respectively. Our study provides a more comprehensive evaluation framework for robust UAV–satellite image matching algorithms in multi-tilt-angle scenarios. Full article

This study addresses key challenges in obtaining reliable infrared data for maritime ship observation and limitations of existing models, such as simplified reflectance assumptions and incomplete multi-band coverage. To improve modeling accuracy and computational efficiency, a high-precision Bidirectional Reflectance and Pseudo-random Vector Enhanced Reverse Monte Carlo Method (BP-ERMCM) is developed. By combining the Bidirectional Reflectance Distribution Function (BRDF), pseudo-random vector approaches, and improved ray-tracking algorithms with precomputed thermal radiation and MODTRAN’s atmospheric transfer model, BP-ERMCM provides multi-view infrared characteristic simulations across 3–5 μm and 8–12 μm bands. Simulations using a 3D ship model with 191 viewpoints reveal seasonal sensitivity, with summer peak intensity at 9.8 μm being 39.3% higher than in winter, and viewpoint dependency showing oblique overhead radiation 5.65 times greater than that from bow angles. Long-wave contours enhance target distinction, while mid-wave regions are dominated by reflection, increasing intensity at 3.8 μm by 56.1–85.7%. These findings highlight BP-ERMCM’s potential to inform infrared signature database construction, detector optimization, and maritime observation strategies. The findings underscore BP-ERMCM’s capability to enhance efficiency and accuracy, providing valuable insights for infrared databases, sensor selection, and maritime observation strategies, thereby advancing infrared signature analysis in maritime applications. Full article