Alignment Uncertainty Research Articles

Trade as a commerical determinant of health: The health impact of a free trade agreement on Wales

Abstract As a result of the UK’s withdrawal from the European Union (‘Brexit’), the UK can negotiate its own trade agreements for the first time in over 40 years. This includes the Comprehensive and Progressive Trans-Pacific Partnership Agreement (CPTPP). Public Health Wales undertook a mixed-method Health Impact Assessment (HIA) to assess the potential impact of the CPTPP on health, well-being and inequalities in Wales. It is only the second ever HIA carried out on a free trade agreement (FTA) globally. A literature review on the potential impact of the CPTPP on health was conducted. Qualitative interviews with cross-sectoral representation, such as the environment, were undertaken alongside the development of a community health and demographic profile. The HIA identified significant potential impacts across health determinants, e.g., employment, agricultural production and health care, as well as impacts on population groups, e.g., those on low incomes. The Investor State Dispute Settlement (ISDS) mechanism, economic uncertainty and loss of regulatory alignment were identified as potential pathways for health impacts to affect the population. The HIA highlighted trade as a key commercial determinant of health. The findings have been beneficial in informing policy and decision-makers to prepare for the implementation of the CPTPP and take action to maximise opportunities and prevent potential negative impacts. Communicating HIA evidence that links trade to health has also led to valuable cross-sector and cross-UK engagement and sparked a “rethinking” of trade through a well-being economy lens where health, well-being and sustainability are primary objectives. This work has demonstrated the value of a HIA approach to FTAs by mobilising a range of evidence through a transparent process, resulting in transferrable learning for others as well providing an entry point for public health to have direct engagement with trade negotiators and those participating in trade discussions. Key messages • Trade agreements are a key commercial determinant of health across health behaviour, policy and economy. • Multiple population groups are affected by trade agreements both positively and negatively.

Identification Uncertainties of Bending Modes of an Onshore Wind Turbine for Vibration-Based Monitoring

This study considers the identification uncertainties of closely spaced bending modes of an operating onshore concrete-steel hybrid wind turbine tower. The knowledge gained contributes to making mode shapes applicable to wind turbine tower monitoring rather than just mode tracking. One reason is that closely spaced modes make it difficult to determine reliable mode shapes for them. For example, the well-known covariance-driven stochastic subspace identification (SSI-COV) yields complex mode shapes with multiple mean phases in the complex plane, which does not allow error-free transformation to the real space. In contrast, the Bayesian Operational Modal Analysis (BAYOMA) allows the determination of real mode shapes. The application of BAYOMA presents a further challenge when quantifying the associated uncertainties, as the typical assumption of a linear, time-invariant system is violated. Therefore, validity is not self-evident and a comprehensive investigation and comparison of results is required. It has already been shown in a previous study that the significant part of the uncertainty in the mode shapes corresponds to their orientation in the mode subspace (MSS). Despite all the challenges mentioned, there is still a great need to develop reliable monitoring parameters (MPs) for Structural Health Monitoring (SHM). This study contributes to this by analysing metrics for comparing mode shapes. In addition to the well-known Modal Assurance Criteria (MAC), the Second-Order MAC (S2MAC) is also used to eliminate the alignment uncertainty by comparing the mode shape with a MSS. In addition, the mode shape identification uncertainties of BAYOMA are also considered. Including uncertainties is also essential for the typically used natural frequencies and damping ratios, which can be more appropriately used if the identification uncertainty is known.

Caustics and velocity caustics in the diffuse interstellar medium at high Galactic latitudes

Context. The far-infrared (FIR) distribution at high Galactic latitudes, observed with Planck, is filamentary with coherent structures in polarization. These structures are also closely related to H I filaments with coherent velocity structures. There is a long-standing debate about the physical nature of these structures. They are considered either as velocity caustics, fluctuations engraved by the turbulent velocity field or as cold three-dimensional density structures in the interstellar medium (ISM). Aims. We discuss different approaches to data analysis and interpretation in order to work out the differences. Methods. We considered mathematical preliminaries for the derivation of caustics that characterize filamentary structures in the ISM. Using the Hessian operator, we traced individual FIR filamentary structures in H I from channel maps as observed and alternatively from data that are provided by the velocity decomposition algorithm (VDA). VDA is claimed to separate velocity caustics from density effects. Results. Based on the strict mathematical definition, the so-called velocity caustics are not actually caustics. These VDA data products may contain caustics in the same way as the original H I observations. Caustics derived by a Hessian analysis of both databases are nearly identical with a correlation coefficient of 98%. However, the VDA algorithm leads to a 30% increase in the alignment uncertainties when fitting FIR/H I orientation angles. Thus, the VDA velocity crowding concept fails to explain the alignment of FIR/H I filaments at |b| > 20°. We used H I absorption data to constrain the physical nature of FIR/H I filaments and determine spin temperatures and volume densities of FIR/H I filaments. H I filaments exist as cold neutral medium (CNM) structures; outside the filaments no CNM absorption is detectable. Conclusions. The CNM in the diffuse ISM is exclusively located in filaments with FIR counterparts. These filaments at high Galactic latitudes exist as cold density structures; velocity crowding effects are negligible.

Distribution analysis of deterministic clamping and positioning error for machining of ring-shaped workpieces considering alignment uncertainty

Distribution analysis of deterministic clamping and positioning error for machining of ring-shaped workpieces considering alignment uncertainty

Characterization of a segmented printed circuit board (PCB) as a standard for absorbed dose to water from alpha-emitting radionuclides.

Our previous work introduced and evaluated a standard for surface absorbed dose rate per unit radioactivity to water from unsealed alpha-emitting radionuclides used in targeted radionuclide therapy (TRT). An overall uncertainty over 4.0% at k=1 was reported for the absorbed dose to air measurements, which was partially attributed to the rotational alignment uncertainty in the geometrical setup. A printed circuit board (PCB) with a segmented guard was constructed to align the extrapolation chamber (EC) and the source plates using a differential capacitance technique. The PCB EC aimed to enhance the repeatability of the ionization current measurements. The PCB EC was evaluated using a thin film 210Po source. The measured absorbed dose to air cavity was compared with the Monte Carlo (MC) calculations. Using the extrapolation method, the surface absorbed dose rate to water was calculated. The PCB EC was constructed with a 4.50mm diameter collector surrounded by four sectors and a guard electrode. The sectors were isolated for rotational alignment and later connected to the guard for ionization current measurements. A bridge circuit measured differential capacitance between opposing sectors, and a hexapod motion stage rotated the source substrate to minimize the differential capacitance. The EC was evaluated using a 210Po source with a 3.20mm diameter and 1.253 Ci radioactivity. MC simulations were performed to calculate the , , and correction factors. Ionization current measurements were performed for air gaps in the 0.3-0.525mm range and surface absorbed dose rate to water was calculated. Rotational offsets of up to 3.0° were found and the current repeatability was found to increase with the absorbed dose to air uncertainty calculated to be ∼2.0%. Using the capacitance method, the effective EC diameter was measured to be 4.53mm. The recombination, polarity, and electrometer corrections were reported to be within 1.00% across all measurement trials. The MC-calculated correction factors were calculated to be much larger than the recombination and polarity correction factors. The average , , and corrections were calculated to be 1.063, 0.9402, and 2.136, respectively. The MC-calculated absorbed dose to air was found to overestimate the absorbed dose by over 4.00% when compared with the measured absorbed dose to air. The surface absorbed dose rate to water was calculated to be Gy/s/Bq with an overall uncertainty of 4.07%. The constructed PCB EC was deemed suitable as an absorbed dose standard. A repeatable rotational alignment was achieved using the differential capacitance technique. The metal electrodes on the PCB made a difference of<1.00% on the backscatter correction when compared to the EC comprised of polystyrene-equivalent collector. A 20% difference in the surface absorbed dose rate to water was found between the two ECs, which is attributed to the cavity diameter differences leading to different magnitudes of dose fall-off along the lateral direction.

Combined Edge Loss UNet for Optimized Segmentation in Total Knee Arthroplasty Preoperative Planning.

Bone segmentation and 3D reconstruction are crucial for total knee arthroplasty (TKA) surgical planning with Personalized Surgical Instruments (PSIs). Traditional semi-automatic approaches are time-consuming and operator-dependent, although they provide reliable outcomes. Moreover, the recent expansion of artificial intelligence (AI) tools towards various medical domains is transforming modern healthcare. Accordingly, this study introduces an automated AI-based pipeline to replace the current operator-based tibia and femur 3D reconstruction procedure enhancing TKA preoperative planning. Leveraging an 822 CT image dataset, a novel patch-based method and an improved segmentation label generation algorithm were coupled to a Combined Edge Loss UNet (CEL-UNet), a novel CNN architecture featuring an additional decoding branch to boost the bone boundary segmentation. Root Mean Squared Errors and Hausdorff distances compared the predicted surfaces to the reference bones showing median and interquartile values of 0.26 (0.19-0.36) mm and 0.24 (0.18-0.32) mm, and of 1.06 (0.73-2.15) mm and 1.43 (0.82-2.86) mm for the tibia and femur, respectively, outperforming previous results of our group, state-of-the-art, and UNet models. A feasibility analysis for a PSI-based surgical plan revealed sub-millimetric distance errors and sub-angular alignment uncertainties in the PSI contact areas and the two cutting planes. Finally, operational environment testing underscored the pipeline's efficiency. More than half of the processed cases complied with the PSI prototyping requirements, reducing the overall time from 35 min to 13.1 s, while the remaining ones underwent a manual refinement step to achieve such PSI requirements, performing the procedure four to eleven times faster than the manufacturer standards. To conclude, this research advocates the need for real-world applicability and optimization of AI solutions in orthopedic surgical practice.

A Dose Accumulation Assessment of Alignment Errors During Spatially Fractionated Radiation Therapy

IntroductionSpatially fractionated radiotherapy (SFRT) techniques produce high-dose peaks and low-dose valleys within a tumor. Lattice stereotactic body radiation therapy (SBRT) is a form a SFRT delivered across five fractions. Due to the high spatial dose gradients associated with SFRT, it is critical for fractionated SFRT patients to be aligned correctly for treatment. Here we investigate the dosimetric impact of daily alignment uncertainty through a dose accumulation study. MethodsDose accumulation was retrospectively performed for ten patients enrolled on a Phase I trial. Lattice SBRT was completed in 5 fractions with 20Gy prescribed to the entire tumor and a simultaneous integrated boost of 66.7Gy prescribed to a set of regularly spaced high-dose spheres. Daily alignment error was quantified through manually selected landmarks in both the planning computed tomography (CT) scan and daily cone-beam CT. The dosimetric impact of alignment errors was quantified by translating the isocenter in the treatment planning system by the daily average alignment error. Large errors were simulated by translating isocenter 5mm and 10mm for one and two fractions, independently assessing errors in the superior-inferior and axial directions. The reduction of dose gradients was quantified using the dose ratio (DR) of the mean dose in the high-dose and low-dose spheres. ResultsThe average alignment error was 1.8mm across the patient population resulting in minor smoothing of the high- and low-dose distributions in the dose accumulation. Quantitatively, the DR decreased from 3.42 to 3.32 (p=0.093) in the dose accumulation study. The simulated worst case was an inferior-superior shift of 10mm for two fractions where the average DR decreased to 2.72 (p=0.0001). ConclusionsThe dose accumulation study revealed on average DR only decreased from 3.42 to 3.32. However, setup errors >5mm resulted in larger dosimetric degradation, reflecting a larger impact for individual high dose spheres within regions exhibiting larger displacements.

How does digital transformation affect sustainable innovation performance? The pivotal roles of digital technology‐business alignment and environmental uncertainty

AbstractDespite the importance of digital transformation in improving sustainable innovation performance, the mechanisms and boundary conditions through which digital transformation affects sustainable innovation performance is unclear. Using the lens of information technology‐enabled organizational capabilities, this study develops a moderated mediation model based on new economic growth theory and information asymmetry theory to examine the impact of digital transformation on sustainable innovation performance. Using a sample of Chinese agriculture firms, our findings reveal that digital transformation positively affects sustainable innovation performance through digital technology‐business alignment, and this indirect effect is stronger when environmental uncertainty is lower. Moreover, environmental uncertainty negatively moderates the relationship between digital transformation and digital technology‐business alignment. Our theoretical explanations and empirical evidence provide insights into how digital transformation initiatives can be leveraged to improve sustainable innovation performance, thus making an important contribution to the related literature.

Uncertainty-Aware Adaptive Semidirect LiDAR Scan Matching for Ground Vehicle Positioning

Iterative Closest Point (ICP) algorithms are widely used in the literature for the estimation of relative transformations using 3D LiDAR point clouds. This class of algorithms proves to be efficient when the 3D data share sufficient overlapping parts and a good initial guess is provided. However, large relative motions and mutual occlusion of objects in real-road scenarios hinder traditional optimization-based ICP from achieving optimal estimation. This paper explores both direct and feature-based 3D LiDAR scan matching using the ICP framework in different contexts, such as parking, residential, urban, and highway scenarios. In order to guarantee the scan matching performances in scenarios with scarce geometric information and fast ego-vehicle motion, we propose an adaptive semi-direct scan matching method together with an alignment uncertainty quantification. The proposed semi-direct scan matching is tested on both the public KITTI and self-recorded LS2N datasets, which accomplishes the robust 6 Degrees of Freedom (DoF) pose estimation and consistent scene reconstruction. We demonstrate that the proposed approach outperforms the state-of-the-art and achieves the leading results with 68.3% average relative fitness and 5.71 cm average RMSE, respectively.

Testing of a custom, portable drill press to minimize probe misalignment in sap flow sensors.

The accurate estimation of plant transpiration is critical to the fields of hydrology, plant physiology and ecology. Among the various methods of measuring transpiration in the field, the sap flow methods based on head pulses offers a cost-effective and energy-efficient option to directly measure the plant-level movement of water through the hydraulically active tissue. While authors have identified several possible sources of error in these measurements, one of the most common sources is misalignment of the sap flow probes due to user error. Though the effects of probe misalignment are well documented, no device or technique has been universally adopted to ensure the proper installation of sap flow probes. In this paper we compare the magnitude of misalignment errors among a 5mm thick drilling template (DT), a 10mm thick DT, and a custom designed, field-portable drill press. The different techniques were evaluated in the laboratory using a 7.5cm wood block and in the field, comparing differences in measured sap flow. Based on analysis of holes drilled in the wood block, we found that the portable drill press was most effective in assuring that drill holes remained parallel, even at 7.5cm depth. In field installations, nearly 50% of holes drilled with a 5mm template needed to be redrilled while none needed to be when drilled with the drill press. Widespread use of a portable drill press when implementing the heat pulse method would minimize alignment uncertainty and allow a clearer understanding of other sources of uncertainty due to variability in tree species, age, or external drivers or transpiration.

Bayesian regional moment tensor from ocean bottom seismograms recorded in the Lesser Antilles: implications for regional stress field

SUMMARY Seismic activity in the Lesser Antilles (LA) is characterized by strong regional variability along the arc reflecting the complex subduction setting and history. Although routine seismicity monitoring can rely on an increasing number of island stations, the island-arc setting means that high-resolution monitoring and detailed studies of fault structures require a network of ocean bottom seismometers (OBS). As part of the 2016–2017 Volatile recycling at the Lesser Antilles arc (VoiLA) project, we deployed 34 OBS stations in the forearc and backarc. During the deployment time, 381 events were recorded within the subduction zone. In this paper, we perform full-waveform regional moment tensor (RMT) inversions, to gain insight into the stress distribution along the arc and at depth. We developed a novel inversion approach, AmΦB—‘Amphibious Bayesian’, taking into account uncertainties associated with OBS deployments. Particularly, the orientation of horizontal components (alignment uncertainty) and the high noise level on them due to ocean microseisms are accounted for using AmΦB. The inversion is conducted using a direct, uniform importance sampling of the fault parameters within a multidimensional tree structure: the uniXtree-sampling algorithm. We show that the alignment of the horizontal OBS components, particularly in high noise level marine environments, influences the obtained source mechanism when using standard least-squares (L2) RMT inversion schemes, resulting in systematic errors in the recovered focal mechanisms including high artificial compensated linear vector dipole (CLVD) contributions. Our Bayesian formulation in AmΦB reduces these CLVD components by nearly 60 per cent and the aberration of the focal geometry as measured by the Kagan angle by around 40 per cent relative to a standard L2 inversion. Subsequently, we use AmΦB-RMT to obtain 45 (Mw &amp;gt; 3.8) regional MT solutions, out of which 39 are new to any existing database. Combining our new results with existing solutions, we subsequently analyse a total of 151 solutions in a focal mechanism classification (FMC) diagram and map them to the regional tectonic setting. We also use our newly compiled RMT database to perform stress tensor inversions along the LA subduction zone. On the plate interface, we observe the typical compressional stress regime of a subduction zone and find evidence for upper-plate strike slip and normal fault behaviour in the north that becomes a near arc-perpendicular extensional stress regime towards the south. A dominant slab perpendicular extensional stress regime is found in the slab at 100–200 km beneath the central part of the arc. We interpret this stress condition to be a result of slab pull varying along the arc due to partial slab detachment along previously hypothesized lateral slab tear near Grenada, at the southern end of the LA arc, leading to reactivation of pre-existing structures around the subducted Proto-Caribbean ridge.

Comparing age model techniques for the last glacial cycle: A case study of ten Iberian Margin sediment cores

Because interpretations of paleoclimate records from ocean sediment cores rely on age models to estimate age as a function of core depth, age model uncertainty can affect the conclusions drawn from paleoclimate data. To assess the age model uncertainty associated with three methods, we compare the age models they generate over the last glacial cycle for high-resolution data from ten western and southern Iberian Margin cores. The first method uses radiocarbon data and the Bayesian statistical software Bacon [Blaauw and Christen, 2011]. The second method aligns benthic δ18O to a target core using the probabilistic alignment algorithm HMM-Match [Lin et al., 2014]. The third method is alignment of planktonic δ18O or sea surface temperature (SST) using the deterministic alignment software Match [Lisiecki and Lisiecki, 2002]. Where three or more age model types overlap in a core, the average range of age estimates is 1.7 kyr, and 90% of age ranges are less than 3 kyr. For the two probabilistic methods, HMM-Match and Bacon, age estimates agree to within uncertainty, and the highest resolution records yield 95% confidence interval widths of 1–2 kyr. However, HMM-Match appears to underestimate alignment uncertainty near gaps in benthic δ18O data in one core, as indicated by disagreement with the core's planktonic δ18O and SST alignments. Planktonic δ18O appears to provide the most precise age models for Iberian Margin cores due to strong millennial-scale variability and good correlation between aligned cores. Probabilistic alignment algorithms should be developed for planktonic δ18O and SST proxies to improve estimates of the age uncertainty for these alignments.

A FIELD-BASED METHOD FOR ESTIMATION OF OVERLAP FOR CONVERGENT IMAGES FOR VIEW PLANNING OF BUILDINGS

Abstract. Overlap between two convergent images for close-range terrestrial photogrammetry is a pre-requisite for view planning of building corners. Available tools determine overlap of images that are acquired by normal geometry at a constant distance. However, for the convergent images lengths of image footprints vary according to camera position. The paper proposes a field-based method that requires to measures only geometric dimensions of image footprints in field for assessing overlap fractions for convergent images. The paper first derives the overlap fraction of convergent images as a function of image footprints, which depend upon the camera position, object geometry, and camera FOV. Experiments are conducted in field for two building corner sites. The proposed method provides conservative estimates of overlap fractions compared to that provided by image-based methods. The errors in the overlap fractions are contributed by three sources, namely, the approximations of the proposed method, uncertainty in camera positions and alignment of camera optical axis, and placement of markers in field. Experimental results suggest that the proposed method can be used confidently in field for overlap estimation for convergent images for the view planning. Images acquired for the view planning of the two corners successfully generated 3D models.

Implications of Multivariate Non-Gaussian Data Assimilation for Multi-scale Weather Prediction

Abstract Weather prediction models currently operate within a probabilistic framework for generating forecasts conditioned on recent measurements of Earth’s atmosphere. This framework can be conceptualized as one that approximates parts of a Bayesian posterior density estimated under assumptions of Gaussian errors. Gaussian error approximations are appropriate for synoptic-scale atmospheric flow, which experiences quasi-linear error evolution over time scales depicted by measurements, but are often hypothesized to be inappropriate for highly nonlinear, sparsely-observed mesoscale processes. The current study adopts an experimental regional modeling system to examine the impact of Gaussian prior error approximations, which are adopted by ensemble Kalman filters (EnKFs) to generate probabilistic predictions. The analysis is aided by results obtained using recently-introduced particle filter (PF) methodology that relies on an implicit non-parametric representation of prior probability densities—but with added computational expense. The investigation focuses on EnKF and PF comparisons over month-long experiments performed using an extensive domain, which features the development and passage of numerous extratropical and tropical cyclones. The experiments reveal spurious small-scale corrections in EnKF members, which come about from inappropriate Gaussian approximations for priors dominated by alignment uncertainty in mesoscale weather systems. Similar behavior is found in PF members, owing to the use of a localization operator, but to a much lesser extent. This result is reproduced and studied using a low-dimensional model, which permits the use of large sample estimates of the Bayesian posterior distribution. Findings from this study motivate the use of data assimilation techniques that provide a more appropriate specification of multivariate non-Gaussian prior densities or a multi-scale treatment of alignment errors during data assimilation.

FlexHDR: Modeling Alignment and Exposure Uncertainties for Flexible HDR Imaging.

High dynamic range (HDR) imaging is of fundamental importance in modern digital photography pipelines and used to produce a high-quality photograph with well exposed regions despite varying illumination across the image. This is typically achieved by merging multiple low dynamic range (LDR) images taken at different exposures. However, over-exposed regions and misalignment errors due to poorly compensated motion result in artefacts such as ghosting. In this paper, we present a new HDR imaging technique that specifically models alignment and exposure uncertainties to produce high quality HDR results. We introduce a strategy that learns to jointly align and assess the alignment and exposure reliability using an HDR-aware, uncertainty-driven attention map that robustly merges the frames into a single high quality HDR image. Further, we introduce a progressive, multi-stage image fusion approach that can flexibly merge any number of LDR images in a permutation-invariant manner. Experimental results show our method can produce better quality HDR images with up to 1.1dB PSNR improvement to the state-of-the-art, and subjective improvements in terms of better detail, colours, and fewer artefacts.

Relative model selection of evolutionary substitution models can be sensitive to multiple sequence alignment uncertainty

BackgroundMultiple sequence alignments (MSAs) represent the fundamental unit of data inputted to most comparative sequence analyses. In phylogenetic analyses in particular, errors in MSA construction have the potential to induce further errors in downstream analyses such as phylogenetic reconstruction itself, ancestral state reconstruction, and divergence time estimation. In addition to providing phylogenetic methods with an MSA to analyze, researchers must also specify a suitable evolutionary model for the given analysis. Most commonly, researchers apply relative model selection to select a model from candidate set and then provide both the MSA and the selected model as input to subsequent analyses. While the influence of MSA errors has been explored for most stages of phylogenetics pipelines, the potential effects of MSA uncertainty on the relative model selection procedure itself have not been explored.ResultsWe assessed the consistency of relative model selection when presented with multiple perturbed versions of a given MSA. We find that while relative model selection is mostly robust to MSA uncertainty, in a substantial proportion of circumstances, relative model selection identifies distinct best-fitting models from different MSAs created from the same set of sequences. We find that this issue is more pervasive for nucleotide data compared to amino-acid data. However, we also find that it is challenging to predict whether relative model selection will be robust or sensitive to uncertainty in a given MSA.ConclusionsWe find that that MSA uncertainty can affect virtually all steps of phylogenetic analysis pipelines to a greater extent than has previously been recognized, including relative model selection.

Fuzzy entity alignment via knowledge embedding with awareness of uncertainty measure

Entity alignment refers to associate entities in different knowledge graphs if they are semantically identical. Embedding-based entity alignment approaches encode entities in a continuous embedding space where entities are aligned based on the similarity of learned embeddings. However, there exists ambiguity and uncertainty in entity alignment caused by single alignment metric. In this paper, a fuzzy entity alignment method FuzzyEA is proposed to model the uncertainty in alignment process based on intuitionistic fuzzy set (IFS). Iterative TransE model is designed to learn relational structure of knowledge graphs, where mutual selection and error correction mechanism is proposed to enhance the effect of iteration. The alignment results obtained by name/description embedding and structure embedding are fused based on Dempster’s combination rule. Experiments on three benchmark datasets demonstrate that the proposed FuzzyEA consistently outperforms other entity alignment methods and contributes to promising improvement in alignment accuracy and discrimination ability.

M3C2-EP: Pushing the limits of 3D topographic point cloud change detection by error propagation

The analysis of topographic time series is often based on bitemporal change detection and quantification. For 3D point clouds, acquired using laser scanning or photogrammetry, random and systematic noise has to be separated from the signal of surface change by determining the minimum detectable change. To analyse geomorphic change in point cloud data, the multiscale model-to-model cloud comparison (M3C2) approach is commonly applied, which provides a statistical significance test. This test assumes planar surfaces and a uniform registration error. For natural surfaces, the planarity assumption does not necessarily apply, in which cases the value of minimal detectable change (Level of Detection) is overestimated. To overcome these limitations, we quantify an uncertainty information for each 3D point by propagating the uncertainty of the measurements themselves and of the alignment uncertainty to the 3D points. This allows the calculation of 3D covariance information for the point cloud, which we use in an extended statistical test for equality of multivariate means. Our method, called M3C2-EP, gives a less biased estimate of the Level of Detection, allowing a more appropriate significance threshold in typical cases. We verify our method in two simulated scenarios, and apply it to a time series of terrestrial laser scans of a rock glacier at two different timespans of three weeks and one year. Over the three-week period, we detect significant change at 12.5% fewer 3D locations, while quantifying additional 25.2% of change volume, when compared to the reference method of M3C2. Compared with manual assessment, M3C2-EP achieves a specificity of 0.97, where M3C2 reaches 0.86 for the one-year timespan, while sensitivity drops from 0.72 for M3C2 to 0.60 for M3C2-EP. Lower Levels of Detection enable the analysis of high-frequency monitoring data, where usually less change has occurred between successive scans, and where change is small compared to local roughness. Our method further allows the combination of data from multiple scan positions or data sources with different levels of uncertainty. The combination using error propagation ensures that every dataset is used to its full potential.

Axis alignment method in the rotating photogrammetric system

In large-scale imaging or measurement, a rotating photogrammetric system with a camera fixed on the surface of the turntable can be used to extend the field of view of the camera with the rotation of the turntable. The camera’s projection center needs to be located at the rotation axis of the turntable, so the images captured during the sequentially rotating share the same projection center. It is very convenient to merge the subimages into a panoramic image. Due to the complexity of the camera’s lens system, the position of the projection center is usually unknown, which makes it difficult to find the projection center and align it with the rotation axis of the turntable. We propose a method to find the distance and azimuth angle between the projection center and rotation axis to solve the alignment problem using the parameters of the camera. In theory, as long as the intrinsic and extrinsic parameters of the camera are known, the distance and angle can be obtained by rotating the turntable once. With the translation values calculated from the distance and angle, the camera can be moved in two directions perpendicular to each other, so its projection center passes through the rotation axis. The theoretical analysis of the alignment problem is given. Experiments verify the feasibility of the proposed method are conducted. The alignment uncertainty of the proposed method is <0.2 mm.

Influence of uncertainty in rail lateral alignment and track lateral resistance on track buckling probability

Influence of uncertainty in rail lateral alignment and track lateral resistance on track buckling probability