Orientation Parameters Research Articles

EXPRESS: Social Profit Orientation: Lessons from Organizations Committed to Building a Better World

Services marketing originated as a discipline to guide managers in marketing intangible products; in today’s world, it must also guide managers in serving society. This research develops the concept of a social profit orientation, whereby organizations invest resources for the express purpose of enhancing the common good, especially the well-being of people and the health of the planet. Implementing social initiatives that serve this broader mission is no small challenge, but exemplary organizations are nevertheless charting a practical course. We interviewed leaders from 21 diverse organizations in multiple countries, spanning both for-profit and nonprofit sectors, yielding valuable insights into how they create social profit for individuals, communities, and society at large through their initiatives. Our research, grounded in published theory and directed toward practical implementation, defines the parameters of a social profit orientation and introduces an innovative framework that distills its antecedents, moderators, and outcomes. The experiences shared by our sample of forward-looking, future-oriented organizations can inform and inspire other companies, organizations, and institutions as they operate in environments where far more is expected of them than ever before.

Updating Orthophotos around Gas Pipelines based on "Cloud Control" Photogrammetry

Abstract. As a clean energy source, natural gas is widely used and primarily transported through long-distance pipelines. Regular maintenance and inspection of long-distance gas pipelines are crucial tasks. Due to the extensive coverage and distance of these pipelines, the workload is enormous. It is necessary to first identify areas of change, which can be carried out using multiple sets of orthophotos produced by unmanned aerial vehicles (UAVs). However, UAV images have small footprints and significant geometric distortions, requiring a large number of ground control points (GCPs) for accurate positioning. Measuring these points in the field is challenging and time-consuming, becoming a key factor limiting the rapid production of orthophotos. To overcome this challenge, this paper introduces the "cloud control" photogrammetry technology to achieve fully automatic updates of orthophotos around long-distance pipelines, providing foundational data for the maintenance and inspection of these gas pipelines. This method replaces GCPs with images containing known orientation parameters, serving as control information. By matching tie points between new and old images, the "cloud control points" are transferred to the new images, enabling the image registration and production of orthophotos. The experiments conducted on the Fumin and Zhaotong segments of a long-distance gas pipeline in Yunnan Province demonstrate that, for UAV images with a ground resolution of 0.05 meters, using the "cloud control" method achieves a planar accuracy of 0.05 meters and an elevation accuracy of 0.07 meters. These results are comparable to the accuracy obtained by orienting the results using GCPs.

On-Orbit Geometric Calibration of the HJ-2 A/B Satellites' Infrared Sensors

Abstract. With the advancement of China's satellite technology, the HuanJingJianZai-2 A/B (HJ-2 A/B) satellites, equipped with whisk-broom infrared sensors, represent a significant leap forward in environmental monitoring and Earth observation capabilities. This technological leap, however, introduces new challenges in calibration. The unique structure of the HJ-2 A/B infrared spectroradiometer (IRS) necessitates innovative calibration techniques, as traditional methods primarily focused on exterior orientation parameters (EOPs) and often overlooked the importance of interior orientation accuracy, which is essential for accurate multispectral band registration and color rendering. Addressing this gap, we introduce an innovative multi-focal-plane-array joint calibration method specifically designed for whisk-broom cameras. Our method involves selecting a master band from each focal plane array for accurate focal length calibration and deriving ground control points from image matching and altitude interpolation for comprehensive bundle adjustment. This adjustment refines EOPs and interior orientation parameters (IOPs), ensuring globally optimal EOPs and enhanced IOPs calibration stability. The application of our method to the HJ-2 A/B IRS yielded substantial improvements in georeferencing and band registration accuracies, surpassing traditional methods. This paper details the multi-focal-plane-array joint calibration method, describes the IRS and experimental setup, presents the experimental results, and concludes with the implications and potential applications of our findings.

Simultaneous Calibration of Multiple Cameras and Generation of Omnidirectional Images

Abstract. Omnidirectional images are increasingly being used in various areas, such as urban mapping, virtual reality, agriculture, and robotics. These images can be generated by different acquisition systems, including multi-camera systems, which can acquire higher-resolution images. Stitching techniques are often used and can be suitable for non-metric applications, but rigorous photogrammetric processing is recommended when having more accurate requirements. The main challenges related to this kind of product are the system calibration and the generation of the final omnidirectional images. When using multi-camera systems, the displacement of the cameras' perspective centres can affect the generation of the omnidirectional images and the resulting accuracy. A common approach to minimising the resulting parallax error is to establish a value for the projection cylinder radius as close as possible to the object's depth. This work proposes a highly accurate simultaneous calibration technique for multiple camera systems using self-calibrating bundle adjustment with constraints of stability of the relative orientation parameters. These parameters are later used to generate a projecting cylindrical surface, maintaining the original camera perspective centres and relative orientation angles. The experiments show that using constraints improved both the calibration results and the final omnidirectional images. Residual mismatches between points in overlapping areas are subpixel.

Dislocations in twistronic heterostructures

Long-period moiré superlattices at the twisted interface of van der Waals heterostructures relax into preferential stacking domains separated by dislocation networks. Here, we develop a mesoscale theory for dislocations in networks formed in twistronic bilayers with parallel (P) and antiparallel (AP) alignment of unit cells across the twisted interface. For P bilayers we find an exact analytical displacement field across partial dislocations and determine analytic dependences of energy per unit length and width on the orientation and microscopic model parameters. For AP bilayers we formulate a semi-analytical approximation for displacement fields across perfect dislocations, establishing parametric dependences for their widths and energies per unit length. In addition, we find regions in the parametric space of crystal thicknesses and Moiré periods for strong and weak relaxation of the Moiré pattern in multilayered twistronic heterostructures.

Calibrating an airborne linear-array multi-camera system on the master focal plane with existing bundled images

ABSTRACT Integrating multiple hyperspectral linear-array cameras into a Linear-array Multi-camera System (LMS) enables an expanded Field of View (FOV) while preserving high spatial resolution. However, the constrained capabilities of tie points are weakened by the limited overlap and short baseline between sub-cameras, hindering the attainment of reliable solutions for the theoretically ideal relative calibration model. Additionally, the absence of stereoscopic imaging in the LMS introduces the challenge of acquiring dense Ground Control Points (GCPs) throughout the FOV during calibration. In this paper, for calibrating an advanced airborne hyperspectral LMS named Arial Hyperspectral System-1000 (AHS-1000), we propose an equivalent geometric model that transforms the three-camera configuration of the LMS into a single-camera representation on the master camera’s focal plane, which was successfully applied to the data processing system of AHS-1000. We extracted dense GCPs by matching each Level-1 sub-image of the LMS with the bundled images of an existing three-line-scanner aerial image dataset, whose orientation parameters have been accurately solved by bundle adjustment with sparse GCPs; the matched points of each sub-image were consistently projected onto the master focal plane as image observations for our equivalent model. Finally, we established a collinearity equation system and performed a combined strip adjustment to calibrate the distortion terms for each pixel of the equivalent camera. The results demonstrate the effectiveness and robustness of our equivalent modeling method, which outperforms the classic modeling method by 2.83 pixels in interior accuracy and 0.86 pixels in relative accuracy, as well as outperforming another similar equivalent modeling method by 1.22 pixels in interior accuracy and 0.18 pixels in relative accuracy. Additionally, our comparison utilizing bundled images, public DOM (Digital Orthophoto Maps) /DEM (Digital Elevation Models), and high-precision DOM/DEM from aerial three-line-scanner demonstrates that bundled images can achieve higher calibration accuracy.

Influence of Printing Angulation on the Accuracy (Trueness and Precision) of the Position of Implant Analogs in 3D Models: An In Vitro Pilot Study

Background: With CAD-CAM, dental models are often fabricated by additive manufacturing (AM) methods. Dental models for implant prostheses involve the manual placement of analogs, which could affect their final fit. Therefore, in this experimental in vitro study, the accuracy of the analogs’ position in models printed using AM methods was examined by comparing three different printing orientations. Methods: An STL file was obtained by scanning a master model with an implant placed in the maxillary left central incisor position. Three study groups (n = 10) with varying printing orientation parameters were obtained (0, 45, and 90 degrees). They were digitalized with a laboratory scanner and evaluated with an analysis metrology program. Differences between 3D datasets were measured using the RMS for trueness and SD RMS for precision. The data were statistically analyzed using the ANOVA test at a significance level of p < 0.05, followed by the Bonferroni post hoc test. Results: The 45-degrees group showed the best results. Regarding trueness, statistically significant differences were found between the 45- and 90-degrees groups (p < 0.005). In terms of precision, statistically significant differences appeared between the 45- and 0-degrees groups (p < 0.011) and between the 45- and 90-degrees groups (0.003). Conclusions: The printing angulation parameter affects the accuracy of 3D-printed models. Implant models manufactured at 45 degrees of printing angulation are more accurate than those printed at 0 or 90 degrees.

Mechanical stability of polarization signatures in biological tissue characterization.

Mueller matrix imaging polarimetry (MMIP) is a promising technique for investigating structural abnormalities in pathological diagnosis. The characterization stability of polarization signatures, described by Mueller matrix parameters (MMPs), correlates with the mechanical state of the biological medium. In this study, we developed an MMIP system capable of applying quantitative forces to samples and measuring the resulting polarization signatures. Mechanical stretching experiments were conducted on a mimicking phantom and a tissue sample at different force scales. We analyzed the textural features and data distribution of MMP images and evaluated the force effect on the characterization of MMPs using the structural similarity index. The results demonstrate that changes in the mechanical microenvironment (CMM) can cause textural fluctuations in MMP images, interfering with the stability of polarization signatures. Specifically, parameters of anisotropic orientation, retardance, and optical rotation are the most sensitive to CMM, inducing a dramatic change in the overall image texture, while other parameters (e.g., polarization, diattenuation, and depolarization) exhibit locality in their response to CMM. For some MMPs, CMM can enhance regional textural contrasts. This study elucidates the mechanical stability of polarization signatures in biological tissue characterization and provides a valuable reference for further research toward minimizing CMM influence.

Evaluation and improvement of Gay-Berne interaction potential to simulate 3D DLVO interaction of clay particles

This paper first presents a set of DLVO-based energy-separation functions for a pair of finite uniformly charged square platelets of infinitesimal thickness in three elementary configurations: face-to-face, edge-to-edge, and edge-to-face. The novel dataset was generated by summing the electrostatic interaction energy computed numerically by solving the non-linear 3D Poisson-Boltzmann equation and the van der Waals interaction energy calculated analytically. The dataset aims to inform qualitatively and quantitatively the energy/force separation functions used in the Discrete Element Method (DEM) and Coarse-Grained Molecular Dynamics (CGMD) modelling of clays. The same dataset was then used to calibrate and evaluate two Gay-Berne (GB)-type potentials: i) a DLVO-adapted Gay-Berne potential, where the Born-van der Waals branches of the underlying Lennard-Jones (LJ) potential are replaced with van der Waals-Columbic branches to represent DLVO interactions; ii) the Mie potential, where the exponents of the two energy terms are ‘unlocked’ instead of being set equal to 12 and 6 as per the original LJ potential. It is shown that the orientation parameter, µ, and the anisotropy parameter, ν, need to be different from µ = 2 and ν = 1 as adopted in CGMD clay modelling to capture the progression of the shape of the pair energy-separation function from face-to-face to edge-to-face and edge-to-edge configuration. It is also shown that the MIE potential (with exponents m = 3 and n = 1.5) better captures the slow decay of the electrostatic repulsive energy component of the DLVO potential energy Coulombic branch of the interaction potential compared to the DLVO-adapted GB potential, which embeds the Lennard-Jones (LJ) exponents m = 12 and n = 6.

Nature and Distribution of Beach Ridges on the Islands of the Greater Caribbean

Beach ridges originate from various depositional processes and occur in a variety of settings. This paper assesses their nature and distribution on the islands of the Greater Caribbean based on a literature review and the identification of sites using Google Earth© 7.3 imagery. The morphological and orientation parameters were measured for each site, and a measure of storm density was developed. These were statistically analysed to develop a classification of beach ridge types. The results show a diversity of beach ridge systems, in terms of setting, morphology, composition and preservation. The presence or absence of an adjacent coral reef is a major differentiating element at the regional level. A regional beach ridge plain classification is proposed, including two main classes, marine beach ridges and river-associated beach ridges, with further sub-divisions based on exposure to hurricanes or hurricanes plus swell waves.

Research on Improved Differential Evolution Particle Swarm Hybrid Optimization Method and Its Application in Camera Calibration

The calibration of cameras plays a critical role in close-range photogrammetry because the precision of calibration has a direct effect on the quality of results. When handling image capture using a camera, traditional swarm intelligence algorithms such as genetic algorithms and particle swarm optimization, in conjunction with Zhang’s calibration method, frequently face difficulties regarding local optima and sluggish convergence. This study presents an enhanced hybrid optimization approach utilizing both the principles of differential evolution and particle swarm optimization, which is then employed in the context of camera calibration. Initially, we establish a measurement model specific to the camera in close-range photogrammetry and determine its interior orientation parameters. Subsequently, employing these parameters as initial values, we perform global optimization and iteration using the improved hybrid optimization algorithm. The effectiveness of the proposed approach is subsequently validated through simulation and comparative experiments. Compared to alternative approaches, the proposed algorithm enhances both the accuracy of camera calibration and the convergence speed. It effectively addresses the issue of other algorithms getting trapped in local optima due to image distortion. These research findings provide theoretical support for practical engineering applications in the field of control theory and optimization to a certain extent.

Bimodal orientation distribution and head-tail asymmetry of a sample of filamentary molecular clouds

ABSTRACT The morphology of molecular clouds is crucial for understanding their origin and evolution. In this work, we investigate the morphology of the filamentary molecular clouds (filaments for short) using a portion of the 12CO(J = 1 − 0) data from the Milky Way Imaging Scroll Painting project. The data cover an area spanning 104.75° < l < 150.25°, |b| < 5.25° in Galactic coordinates, with VLSR ranging from −95 to 25 kms−1. Our primary focus is on the orientation and morphological asymmetry of the filaments. To achieve this, we apply several criteria on the data to create a sample of filaments with well-defined straight shape, and we use elliptical fitting to obtain the orientation of each filament, with an estimated error of ∼1.6° for the orientation. We find that the filament orientation with respect to the Galactic plane exhibits a bimodal distribution, a double-Gaussian fitting of which has two centres located at −38.1° and 42.0°, with 1σ of the two Gaussian functions being 35.4° and 27.4°. We do not find significant correlation between the orientation and other parameters, including the Galactic coordinates, radial velocity, velocity width, and physical scale. A considerable fraction of filaments (≳40 per cent) display head-tail asymmetry, which suggests that mass concentration tends to occur at one end of the filaments.

X-ray tomography applied to tsunami deposits: Optimized image processing and quantitative analysis of particle size, particle shape, and sedimentary fabric in 3D

The analysis of particle size, shape, size, and their spatial arrangement (i.e. fabric) in a sedimentary deposit plays a significant role in their interpretation in terms of transport mechanism, flow conditions, and sediment source. The present work focuses on the use of X-ray computed tomography (X-CT) to analyze tsunami deposits (core samples), as examples of complex sedimentary assemblages. A workflow of image processing is proposed to measure 3D parameters of particle size, shape, and orientation using two different software packages (Fiji-ImageJ, and IPSDK) and two different methods of image segmentation. The semi-automated method provides better segmentation quality of the tsunami deposit, as compared with the poor performance of fully-automated image segmentation. We also provide some clues to reduce the computational time. This workflow is applied to two examples of tsunami deposits on the coasts of the Algarve (1755 Lisbon tsunami, southern Portugal). Optimized processing of X-CT images gives access to detailed vertical variations of grain size, grain shape, and componentry (clayey matrix, silicates, and carbonates, including marine bioclasts), as well as information on flow directions inferred from the sedimentary fabric in 3D. High-resolution analysis of the bedforms and vertical grain size grading allows determining the flow conditions during the inundation phase of the tsunami.

Assessment of length-of-day and universal time predictions based on the results of the Second Earth Orientation Parameters Prediction Comparison Campaign

Predicting Earth Orientation Parameters (EOP) is crucial for precise positioning and navigation both on the Earth’s surface and in space. In recent years, many approaches have been developed to forecast EOP, incorporating observed EOP as well as information on the effective angular momentum (EAM) derived from numerical models of the atmosphere, oceans, and land-surface dynamics. The Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC) aimed to comprehensively evaluate EOP forecasts from many international participants and identify the most promising prediction methodologies. This paper presents the validation results of predictions for universal time and length-of-day variations submitted during the 2nd EOP PCC, providing an assessment of their accuracy and reliability. We conduct a detailed evaluation of all valid forecasts using the IERS 14 C04 solution provided by the International Earth Rotation and Reference Systems Service (IERS) as a reference and mean absolute error as the quality measure. Our analysis demonstrates that approaches based on machine learning or the combination of least squares and autoregression, with the use of EAM information as an additional input, provide the highest prediction accuracy for both investigated parameters. Utilizing precise EAM data and forecasts emerges as a pivotal factor in enhancing forecasting accuracy. Although several methods show some potential to outperform the IERS forecasts, the current standard predictions disseminated by IERS are highly reliable and can be fully recommended for operational purposes.

Cryo-forum: A framework for orientation recovery with uncertainty measure with the application in cryo-EM image analysis

In single-particle cryo-electron microscopy (cryo-EM), efficient determination of orientation parameters for particle images poses a significant challenge yet is crucial for reconstructing 3D structures. This task is complicated by the high noise levels in the datasets, which often include outliers, necessitating several time-consuming 2D clean-up processes. Recently, solutions based on deep learning have emerged, offering a more streamlined approach to the traditionally laborious task of orientation estimation. These solutions employ amortized inference, eliminating the need to estimate parameters individually for each image. However, these methods frequently overlook the presence of outliers and may not adequately concentrate on the components used within the network. This paper introduces a novel approach that uses a 10-dimensional feature vector to represent the orientation and applies a Quadratically-Constrained Quadratic Program to derive the predicted orientation as a unit quaternion, supplemented by an uncertainty metric. Furthermore, we propose a unique loss function that considers the pairwise distances between orientations, thereby enhancing the accuracy of our method. Finally, we also comprehensively evaluate the design choices in constructing the encoder network, a topic that has not received sufficient attention in the literature. Our numerical analysis demonstrates that our methodology effectively recovers orientations from 2D cryo-EM images in an end-to-end manner. Notably, the inclusion of uncertainty quantification allows for direct clean-up of the dataset at the 3D level. Lastly, we package our proposed methods into a user-friendly software suite named cryo-forum, designed for easy access by developers.

Study on anisotropy orientation due to well-ordered fibrous biological microstructures.

Most biological fibrous tissues have anisotropic optical characteristics, which originate from scattering by their fibrous microstructures and birefringence of biological macromolecules. The orientation-related anisotropic interpretation is of great value in biological tissue characterization and pathological diagnosis. We focus on intrinsic birefringence and form birefringence in biological tissue samples. By observing and comparing the forward Mueller matrix of typical samples, we can understand the interpretation ability of orientation-related polarization parameters and further distinguish the sources and trends of anisotropy in tissues. For glass fiber, silk fiber, skeletal muscle, and tendon, we construct a forward measuring device to obtain the Mueller matrix image and calculate the anisotropic parameters related to orientation. The statistical analysis method based on polar coordinates can effectively analyze the difference in anisotropic parameters. For those birefringent fibers, the statistical distribution of fast-axis values derived from Mueller matrix polar decomposition was found to exhibit bimodal characteristics, which is a key point in distinguishing the single-layer birefringent fiber sample from a layered, multioriented fibrous sample. The application conditions and interference factors of anisotropic orientation parameters are analyzed. Based on the parameters extracted from the orientation bimodal distribution, we can evaluate the relative change trend of intrinsic birefringence and form birefringence in anisotropic samples. The cross-vertical bimodal distribution of the fast axis of anisotropic fibers is beneficial to accurately analyze the anisotropic changes in biological tissues. The results imply the potential of anisotropic orientation analysis for applications in pathological diagnosis.

3D Modeling of Façade Elements Using Multi-View Images from Mobile Scanning Systems

There is a growing demand for detailed building façade models (Level-of-Detail 3: LoD 3) in a variety of applications. Despite the increasing number of papers addressing this issue in the literature, occlusions are still a significant problem when processing building façade elements. Conversely, depending on the view angle of the images, the detected elements might not be projected to their accurate locations causing uncertainties in their 3D locations. In this paper, we address the aforementioned issues utilizing multi-view images. Using a building footprint layer, we first locate the points belonging to buildings. We then detect the 2D windows and doors in images by combining Faster R-CNN and Segment Anything (SAM) deep learning models. The 2D borders are projected into the 3D object space using a pinhole camera model and collinearity equations. Utilizing the multi-view capabilities of mobile scanning systems, this method effectively mitigates uncertainties associated with occlusion and exterior orientation parameters (EOP). This study provides a comprehensive evaluation of 3D spatial accuracy, achieving an average of 84% Intersection over Union (IoU) accuracy for 12 different single-sided façades over 750 multi-view images for 312 windows and doors of various sizes with rectangular and curved shapes.

Automatic Design of Serial Linkage Using Virtual Screw Joint

Here, an automatic design method for a serial link mechanism is proposed. This method outputs all kinematic parameters of joints, position, orientation, number, and type of joint (revolute or prismatic). Several studies have been conducted on optimizing only the positions and directions of joints for a desired path. However, automatically determining the numbers and types of joints requires an excessive calculation time owing to the complicity of kinematics. To handle heavy computation, a virtual screw joint (VSJ) is introduced based on a screw axis and the product of exponentials formula. Screw joints have the advantage of including both rotation and translation. First, an additional joint is optimized as a VSJ. Then, adopting its position and orientation and selecting a revolute or prismatic joint facilitate an efficient design process. To demonstrate the effectiveness of this study, two task motions addressed in a related work are adopted as target paths. Consequently, the proposed method automatically generates serial linkages that contain both revolute and prismatic joints and can follow along desired paths.

Effect of natural fracture on the heat mining of enhanced geothermal system based on the thermo-hydro-mechanical coupling model

ABSTRACT Hydraulic fracture, natural fracture and fracture networks play a vital role for heat mining of Enhanced Geothermal System (EGS). In this work, a two-dimensional thermo-hydro-mechanical (THM) EGS model was proposed to investigate the effect of natural fracture on heat extraction performance. Based on the local thermal non-equilibrium theory and discrete natural fracture network, the spatial and temporal distribution of temperature, pore pressure, effective stress, rock matrix porosity and permeability are investigated. The results show that the natural fracture has a significant negative effect on the production temperature. After the 40-year prediction, the production temperature of the base model is 45.5°C lower than that of the without natural fracture model. In the initial operation stage, the low-temperature region is mainly distributed in the region of artificial fracture and injection well, then it expands significantly to the natural fracture due to the stress redistribution. The key parameters of quantity and orientation of natural fracture can lead to a decline in production temperature and earlier thermal breakthroughs within the thermal reservoir.

MULTIMEDIA PHOTOGRAMMETRY 2.0. A FIRST STEP FOR UNDERWATER CULTURAL HERITAGE APPLICATION

Abstract. The research is framed in multimedia photogrammetry, a specific domain aimed at acquiring geometric information about static objects immersed or semi-submerged in a liquid through one or more cameras external to the liquid. If the liquid is water, this field belongs to the broader field of applied metrology for analysing and understanding the aquatic world. Specifically, the various passive sensing techniques for acquiring Underwater Cultural Heritage (UCH) in shallow water are central to understanding the research domain's underlying issues. Our research is framed in the domain, implementing the automatic analysis to estimate a priori (and correcting a posteriori) the camera's behaviour under certain conditions for acquiring submerged or semi-submerged objects. The first analytical results are framed in a two-year project, which aims to define a behaviour model in a controlled environment with encoded targets and stereo-photogrammetry, automatically extracting the camera orientation parameters under different water height conditions. A planar reproduction of a CH artefact, which simulates an immersed architectonic floor, has been applied to validate the process in a first case study, testing the system's capacity to extract the correct coordinates of the image. At the end of this first experimental phase, the aim is to define a model for the behaviour of water deformation. It will make it possible to predict and correct the water refraction by calculating the correct coordinates within the liquid. In the future, this model will be tested under different and incrementally more complex acquisition conditions. The global project's primary goal is to arrive at the application of this model in an uncontrolled environment for the survey of UCH in shallow water.