Geometric Data Research Articles

Fourier representation of geometrical imperfection for probabilistic buckling analysis

This research studies the first part of the failure of a compression member structure due to buckling. This unstable equilibrium collapse, exposes brittle failure which occurs suddenly and therefore should be avoided wherever possible. Unavoidable geometric imperfections due to structural fabrication, will weaken the structure against buckling. The behavior of bar under compression will be closely examined by taking a set of geometric imperfection data synthesized from previously available from the measurement of conical shells. Therefore, the two-dimensional surface imperfection is converted into several one-dimensional imperfection with some probability properties. In order to obtain a comparison tool for different type of imperfections, Fourier analysis is used to convert the imperfection into coefficients of trigonometric function. By examining the coefficients, geometric imperfection patterns introduced by a certain fabrication process are able to be identified. The study successfully demonstrates the applicability of Fourier analysis in representing inherent geometric imperfections as an initial step for conducting probabilistic buckling analysis. Fourier analysis has shown its capability to simultaneously characterize imperfections in two crucial parameters - the magnitude and configuration of the imperfection.

Efficient Multi-Object Tracking Using RNN and Siamese Re-Identification

This work presents a comprehensive study and methodology to cope the problem of multi-object tracking. The methodology proposed here aims to simplify the problem space by using RNN as a regression network for predicting current object tracker information from past data and using Siamese network for re-identification. The number of re-identification is reduced by doing suboptimal perfect matching using a tree data structure for geometric location data of objects in view port.

Parallel phenotypic evolution of two independent cavefish lineages of Astyanax mexicanus (De Filippi, 1854) (Characiformes: Characidae)

Abstract Astyanax mexicanus offers a unique model for studying parallel evolution, with cave-dwelling forms arising from at least two distinct surface lineages. Here, we examined repeated evolution in the two cave-adapted lineages across four phenotypic datasets: (i) meristic data; (ii) ecomorphological data; and geometric morphometric data for (iii) head and (iv) premaxillary bone shape. Additionally, we assessed the association of these phenotypes with their phylogenetic history. Certain traits exhibited evidence of parallel evolution for the cave ecotype across lineages, such as increased maxillary tooth count, reduced lateral line scale count, and shorter ascending process of the premaxillary bone. Geometric morphometric data showed a phenotypic divergence gradient in head shape between cave and surface populations, with the strongest divergence between Sierra de El Abra and surface populations and with less differentiation between surface populations and caves from Sierra de Guatemala and Micos. Cave populations that hybridize with surface populations (e.g. Micos) displayed the greatest overlap with the surface ecotype. There was a similar divergence gradient for premaxillary bone shape, but with weaker differentiation between cave and surface ecotypes. This evidence of repeated evolution in several cave traits emphasizes the significance of selective pressures exerted by the environment on the evolution of cave ecotypes.

An integrated method and tool for telescopic beams design in extendable undercarriages

Earth-moving machine builders require innovative design methods and tool to optimize structural performance while reducing production and design costs, particularly in crucial phases like undercarriage frame design and structural verification. After an in-depth description of the design flow normally followed in industry, the paper presents a computationally efficient method and tool to aid designers in dimensioning extendable tracked undercarriages, aiming to drastically reduce design time and efforts to optimize resources. The proposed tool is based on an analytical model established from in-depth analyses of the undercarriage Computer Aided Design (CAD) assembly and the expertise of the industrial partner. To address the 3D structural problem, a planar system is employed with proper corrective coefficients. These coefficients are meticulously evaluated through direct comparison with Finite Element Method (FEM) models by seamlessly integrating SolidWorks and ANSYS Workbench. The tool accepts as inputs geometric and material data, as well as specific user-defined load scenarios, providing outputs in the form of the deflected configuration of the undercarriage and stress levels. Direct comparison with the results obtained from FEM for three industrial undercarriage models demonstrates the validity of the approach, with errors consistently within the 10% range in almost all cases. This enables designers with no advanced skills in FEM to efficiently validate diverse design variants with minimal effort. Once validated, the tool is integrated with an optimizer in Matlab to conduct computationally efficient design optimization studies. The optimization problem, focused on minimizing the beam’s vertical size while maintaining structural integrity and limiting deflections, has been successfully resolved within a limited computational time, showcasing the benefits of the proposed approach for undercarriage design.

THE AIRCRAFT ENGINE PROPELLER MAIN CHARACTERISTICS DETERMINATION IMPROVED METHOD

An improved method of the fixed and variable pitch propeller aerodynamic characteristics determining that based on the vortex theory is presented. It is shown that the design of propellers has it`s peculiarities, it does not take into account a number of factors that affect the propeller operation to one or another degree. This actualized the special purpose unmanned aerial vehicles engines propellers aerodynamic characteristics calculating methodology improvement. Since the use of the propeller profiles performances in the design requires the air compressibility correction introduction already after the selection of the propeller, that complicates the design, therefore the mathematical model of the variable-pitch propeller working process has been improved based on the profile model with the correct consideration of the Mach and Reynolds numbers influence on the aerodynamic characteristics of the air screw. This advantage of the developed airfoil model allows the design and verification of a subsonic propeller for ground and flight operations. Methods of design and verification calculations of propeller blades are presented. Verification of the improved methodology was carried out by comparing calculated data with known experimental data. The reliability of the improved aircraft engine propeller main performances determination methodology is substantiated by the correct application of the numerical and experimental methods of aerodynamics, the consistency of theoretical provisions with experimental data. The satisfactory coincidence of the calculated data obtained by the improved method of the engine propeller main performances determination allowed us to draw a conclusion concerning its efficiency. The improved technique for the main performances of an aircraft engine propeller determination does not require knowledge on the propeller profiles aerodynamic characteristics from which the blade is drawn, since these characteristics are calculated based on known geometric data, taking into account the Mach and Reynolds numbers. This allows you to design and build a subsonic propeller of both fixed pitch and variable pitch.

Improved Video-Based Point Cloud Compression via Segmentation.

A point cloud is a representation of objects or scenes utilising unordered points comprising 3D positions and attributes. The ability of point clouds to mimic natural forms has gained significant attention from diverse applied fields, such as virtual reality and augmented reality. However, the point cloud, especially those representing dynamic scenes or objects in motion, must be compressed efficiently due to its huge data volume. The latest video-based point cloud compression (V-PCC) standard for dynamic point clouds divides the 3D point cloud into many patches using computationally expensive normal estimation, segmentation, and refinement. The patches are projected onto a 2D plane to apply existing video coding techniques. This process often results in losing proximity information and some original points. This loss induces artefacts that adversely affect user perception. The proposed method segments dynamic point clouds based on shape similarity and occlusion before patch generation. This segmentation strategy helps maintain the points' proximity and retain more original points by exploiting the density and occlusion of the points. The experimental results establish that the proposed method significantly outperforms the V-PCC standard and other relevant methods regarding rate-distortion performance and subjective quality testing for both geometric and texture data of several benchmark video sequences.

A smartphone application for personalized facial aesthetic monitoring.

Methods available at home for capturing facial images to track changes in skin quality and evaluate skincare treatments are limited. In this study, we developed a smartphone camera application (app) for personalized facial aesthetic monitoring. A face alignment indicators (FAIN) system utilizing facial landmark detection, an artificial intelligence technique, to estimate key facial parts, was implemented into the app to maintain a consistent facial appearance during image capture. The FAIN system is composed of a fixed target indicator and an alignment indicator that dynamically changes its shape according to the user's face position, size, and orientation. Users align their faces to match the alignment indicator with the fixed target indicator, and the image is automatically captured when alignment is achieved. We investigated the app's effectiveness in ensuring a consistent facial appearance by analyzing both geometric and colorimetric data. Geometric information from captured faces and colorimetric data from stickers applied to the faces were utilized. The coefficients of variation (CVs) for the L*, a*, and b* values of the stickers were higher compared to those measured by a colorimeter, with CVs of 14.9 times, 8.14 times, and 4.41 times for L*, a*, and b*, respectively. To assess the feasibility of the app for facial aesthetic monitoring, we tracked changes in pseudo-skin color on the cheek of a participant using skin-colored stickers. As a result, we observed the smallest color difference ∆Eab of 1.901, which can be considered as the experimentally validated detection limit using images acquired by the app. While the current monitoring method is a relative quantification approach, it contributes to evidence-based evaluations of skincare treatments.

Battles and crossings of methods: Sequence analysis and geometric data analysis for the study of professional careers

This article proposes to discuss the exploratory use of two quantitative methods: on the one hand sequence analysis combined with optimal matching methods, and on the other hand geometric data analysis, more specifically multiple correspondence analysis and principal component analysis, combined with hierarchical ascending classifications. The aim is not to determine whether one method is more effective than another, nor to pit them against each other. The aim is to identify similarities and differences, and, more generally, to reflect on the cross-use of quantitative methods. The approach is decidedly practical and reflective. It consists of opening up the kitchen of implementation through a case study: build a typology of the professional futures of the accredited parliamentary assistants at the European Parliament. The paper defends the idea that typologies are tools and stages in analysis. Putting these methods to the test in this way aims to highlight several issues, suggest avenues of analysis, and highlight the need to explore the data using a variety of tools. This text is an invitation to compare and combine methods, and to use them in a considered and non-mechanical way, taking into account their strengths but also their weaknesses, which are also instructive.

Accurate Registration of Cross-Modality Geometry via Consistent Clustering.

The registration of unitary-modality geometric data has been successfully explored over past decades. However, existing approaches typically struggle to handle cross-modality data due to the intrinsic difference between different models. To address this problem, in this article, we formulate the cross-modality registration problem as a consistent clustering process. First, we study the structure similarity between different modalities based on an adaptive fuzzy shape clustering, from which a coarse alignment is successfully operated. Then, we optimize the result using fuzzy clustering consistently, in which the source and target models are formulated as clustering memberships and centroids, respectively. This optimization casts new insight into point set registration, and substantially improves the robustness against outliers. Additionally, we investigate the effect of fuzzier in fuzzy clustering on the cross-modality registration problem, from which we theoretically prove that the classical Iterative Closest Point (ICP) algorithm is a special case of our newly defined objective function. Comprehensive experiments and analysis are conducted on both synthetic and real-world cross-modality datasets. Qualitative and quantitative results demonstrate that our method outperforms state-of-the-art approaches with higher accuracy and robustness. Our code is publicly available at https://github.com/zikai1/CrossModReg.

Interpolation by decomposable univariate polynomials

The usual univariate interpolation problem of finding a monic polynomial f of degree n that interpolates n given values is well understood. This paper studies a variant where f is required to be composite, say, a composition of two polynomials of degrees d and e, respectively, with de=n, and with d+e−1 given values. Some special cases are easy to solve, and for the general case, we construct a homotopy between it and a special case. We compute a geometric solution of the algebraic curve presenting this homotopy, and this also provides an answer to the interpolation task. The computing time is polynomial in the geometric data, like the degree, of this curve. A consequence is that for almost all inputs, a decomposable interpolation polynomial exists.

Enabling personalized VR experiences: a framework for real-time adaptation and recommendations in VR environments

The personalization of user experiences through recommendation systems has been extensively explored in Internet applications, but this has yet to be fully addressed in Virtual Reality (VR) environments. The complexity of managing geometric 3D data, computational load, and natural interactions poses significant challenges in real-time adaptation in these immersive experiences. However, tailoring VR environments to individual user needs and interests holds promise for enhancing user experiences. In this paper, we present Virtual Reality Environment Adaptation through Recommendations (VR-EAR), a framework designed to address this challenge. VR-EAR employs customizable object metadata and a hybrid recommendation system modeling implicit user feedback in VR environments. We utilize VR optimization techniques to ensure efficient performance. To evaluate our framework, we designed a virtual store where product locations dynamically adjust based on user interactions. Our results demonstrate the effectiveness of VR-EAR in adapting and personalizing VR environments in real time. domains.

Geometric data analysis-based machine learning for two-dimensional perovskite design

With extraordinarily high efficiency, low cost, and excellent stability, 2D perovskite has demonstrated a great potential to revolutionize photovoltaics technology. However, inefficient material structure representations have significantly hindered artificial intelligence (AI)-based perovskite design and discovery. Here we propose geometric data analysis (GDA)-based perovskite structure representation and featurization and combine them with learning models for 2D perovskite design. Both geometric properties and periodicity information of the material unit cell, are fully characterized by a series of 1D functions, i.e., density fingerprints (DFs), which are mathematically guaranteed to be invariant under different unit cell representations and stable to structure perturbations. Element-specific DFs, which are based on different site combinations and atom types, are combined with gradient boosting tree (GBT) model. It has been found that our GDA-based learning models can outperform all existing models, as far as we know, on the widely used new materials for solar energetics (NMSE) databank.

Computational Investigation about the Effects of Solvent Polarity and Chalcogen Element Electronegativity on ESIPT Behaviors for the Et2N-Substituted Flavonoid.

Inspired by the outstanding nature of flavonoid derivatives in the fields of chemistry and medicine, in this work we mainly focus on exploring the photo-induced properties of the novel Et2N-substituted flavonoid (ENF) fluorophore theoretically. Considering the potential photo-induced properties in different solvents and the chalcogen atomic electronegativity-associated photoexcitation, by time-dependent density functional theory (TDDFT) methods we primarily explore the intramolecular hydrogen bonding interactions and photo-induced charge redistribution behaviors. Via comparing geometrical data and the infrared (IR) spectral shifts-associated hydroxy moiety of ENF, we confirm that the intramolecular hydrogen bond O-H···O should be enhanced with facilitating an excited-state intramolecular proton-transfer (ESIPT) reaction. Particularly, the charge reorganization around hydrogen bonding moieties further reveals the tendency of ESIPT behavior. Combined with the construction of the potential energy surface and the search for reaction transition states, we finally confirmed the solvent-polarity-regulated behaviors as well as the chalcogen elements' electronegativity-dependent ESIPT mechanisms for the ENF fluorophore. We sincerely wish our work could accelerate the further development and applications of flavonoid derivatives.

Rapid measurement method for cable tension of cable‐stayed bridges using terrestrial laser scanning

AbstractThis study proposes a new method for the rapid and non‐contact measurement of cable forces in cable‐stayed bridges, including a cable force calculation method based on measured cable shapes and a batch acquisition method for the true shape of cables. First, a nonlinear regression model for estimating cable forces based on measured cable shapes is established, and a Gauss–Newton‐based cable force solving method is proposed. Furthermore, terrestrial laser scanning technology is used to collect geometric data of the cables. Meanwhile, automatic segmentation, noise reduction, and centerline extraction algorithms for the cable point cloud are proposed to accurately and efficiently obtain the cable shape. The correctness of the proposed cable force calculation method is verified in a well‐designed experiment, with the measurement error of cable forces for 15 test samples being less than 1%. Finally, the proposed point cloud automation processing algorithm and cable force measurement method are fully tested on a cable‐stayed bridge with a span of 460 m. The measurement accuracy of the proposed method for actual bridge cable tension is comparable to that of the frequency method, but the detection efficiency on site is nine times higher than that of the traditional frequency method. Overall, this study provides a new measurement method for construction control, health monitoring, intelligent detection, and other fields of cable‐stayed bridges.

Original or post-war paintings? The fixed wooden scenery of the Teatro Olimpico in Vicenza: a guided multidisciplinary approach based on scientific analyses and HBIM

Archival resources, a photogrammetric survey, analysis of materials and techniques, and evaluation of the state of conservation were interconnected phases in the interdisciplinary research on the perspective scenery of the Teatro Olimpico in Vicenza. To fill existing gaps related to the history of this unique artefact and to the undocumented retouching of paint layers on the scenery during post-war reconstruction work, a broad analytical approach (optical microscopy, XRPD, SEM–EDX, μFTIR and μRaman) was applied to micro-samples, the selection of which was guided by consolidated geometrical and archival data. The aims were to obtain a characterisation of the pigments and binders and to evaluate the microstratigraphic sequence, the state of conservation of the scenery flats, and the deterioration processes involved. The findings unveiled a discernible variability in the production techniques of the finishes, frequently lacking the classic microstratigraphic sequence associated with the traditional method for painting on wooden panels from the sixteenth century. Moreover, by identifying many pigments that could be used as temporal markers we were able unequivocally to establish, for the first time, that a significant part of the scenery designed by the architect Vincenzo Scamozzi was heavily repainted in the post-WWII period. These analytical results and all the data collected on the artefacts over time were related through an HBIM model, enabling the historical and technical-analytical information to be linked to the geometrical survey and thus to provide guidance for actions based on current and future knowledge for the maintenance and monitoring of the Teatro Olimpico.

Digital Twin Smart City: Integrating IFC and CityGML with Semantic Graph for Advanced 3D City Model Visualization

The growing interest in building data management, especially the building information model (BIM), has significantly influenced urban management, materials supply chain analysis, documentation, and storage. However, the integration of BIM into 3D GIS tools is becoming more common, showing progress beyond the traditional problem. To address this, this study proposes data transformation methods involving mapping between three domains: industry foundation classes (IFC), city geometry markup language (CityGML), and web ontology framework (OWL)/resource description framework (RDF). Initially, IFC data are converted to CityGML format using the feature manipulation engine (FME) at CityGML standard’s levels of detail 4 (LOD4) to enhance BIM data interoperability. Subsequently, CityGML is converted to the OWL/RDF diagram format to validate the proposed BIM conversion process. To ensure integration between BIM and GIS, geometric data and information are visualized through Cesium Ion web services and Unreal Engine. Additionally, an RDF graph is applied to analyze the association between the semantic mapping of the CityGML standard, with Neo4j (a graph database management system) utilized for visualization. The study’s results demonstrate that the proposed data transformation methods significantly improve the interoperability and visualization of 3D city models, facilitating better urban management and planning.

Exploring interacting effects of risk factors on run-off-road crash severity: An interpretable machine learning model joint with latent class clustering

Run-Off-Road (ROR) crashes are frequent and pose a significant risk of injury and fatality. Given the complexity of their mechanisms and the interaction of multiple factors, this study aims to comprehensively investigate the factors influencing the severity of ROR crashes, which have been understudied. Furthermore, addressing the current methodological challenge in machine learning (ML) crash modeling, this study proposes an approach to tackle unobserved heterogeneity in ML. An interpretable ML joint with prior latent class clustering is implemented. The significant risk factors and interactions are interpreted using SHAP (SHapley Additive exPlanations) method across clusters. This study utilizes ROR crash records, traffic, and geometric data from main suburban freeways in Iran collected over a 5-year period. The key interacting factors associated with severe ROR during adverse weather (cluster 1) are: co-occurrence of low congestion and higher speed variation; low congestion, nighttime darkness and rollover; roadway departure by buses and mini-buses and rollover occurrence; vehicle departure and collision with fixed objects. Moreover, the critical interactions for nighttime condition (cluster 2) are: curve sections combined with longitudinal slope; inside shoulder width <1.5 m and a hit median concrete NewJersey barrier. The risky interactions for crashes occurred in curves (cluster 3) are: departing in two-lane sections in low congestion conditions; vehicles collisions with the median concrete NewJersey barriers. The findings of this study enhance comprehension of the significant effects of interactions under various conditions, offering valuable insights for policymakers. Additionally, recommendations are offered to mitigate the risk of severe ROR crashes.

Implementation of an Automated Code Checking Algorithm Based on Site Analysis

To date, BIM has been primarily utilized in cost and schedule management, an interference check between architectural and structural models and systems based on geometric data in the process of the construction life cycle. However, there is a lack of research that utilizes the information contained in the BIM model to review whether the proposed architectural model is appropriately designed in accordance with each country’s building regulations or building codes or that proposes a model optimized for laws and standards. ‘Building code checking’ is the step of reviewing whether a building designed based on the building codes is suitable for being constructed as a building. However, this process consumes significant time and money and leads to human errors due to the manual review process. This study included implementation of an algorithm based on the Korean building code. In this study, there was the process of selection of codes when architects interpret building codes in common and implementation based on the codes selected. Next, modeling based on DXF files from NGII (National Geographic Information Institute) was applied to the algorithm developed in this study. Last, it includes case studies that compare the outputs of the algorithm with the real buildings, which had received real code checking, to make sure the algorithm in this paper is working properly. The implementation of such an automated system has the potential to significantly improve the efficiency and effectiveness of the building design and construction process. It can help architects to quickly and accurately identify potential legal issues and provide alternative solutions that meet regulatory requirements. This, in turn, can lead to reduced project costs, improved quality of designs, and faster project delivery times.

Horizons that gyre and gimble: a differential characterization of null hypersurfaces

Motivated by the thermodynamics of black hole solutions conformal to stationary solutions, we study the geometric invariant theory of null hypersurfaces. It is well-known that a null hypersurface in a Lorentzian manifold can be treated as a Carrollian geometry. Additional structure can be added to this geometry by choosing a connection which yields a Carrollian manifold. In the literature various authors have introduced Koszul connections to study the study the physics on these hypersurfaces. In this paper we examine the various Carrollian geometries and their relationship to null hypersurface embeddings. We specify the geometric data required to construct a rigid Carrollian geometry, and we argue that a connection with torsion is the most natural object to study Carrollian manifolds. We then use this connection to develop a hypersurface calculus suitable for a study of intrinsic and extrinsic differential invariants on embedded null hypersurfaces; motivating examples are given, including geometric invariants preserved under conformal transformations.

Improving a regional project on diagnostic reference levels for interventional procedures (OPRIPALC) with the support of a dose management system for the protection of patients and staff

Interventional radiology is a clinical practice with important benefits for patients, but which involves high radiation doses. The optimisation of radiation protection (RP) for paediatric interventional cardiology is a priority for both patients and staff. The use of diagnostic reference levels (DRLs) has been proposed by the International Commission on Radiological Protection to improve RP in imaging procedures. Dose management systems (DMSs) allow the automatic collection of dosimetric, geometric and technical data to assist the optimisation process, with a continuous audit of the procedures, generating alerts to implement corrective actions when necessary. Patient dose indicators may be analysed individually and for different radiation events (fluoroscopy and cine runs). Occupational doses per procedure may be analysed (if electronic dosimeters are available) and linked with patient doses for an integrated approach to RP. Regional optimisation programmes require data collection and processing from several countries to set and periodically update the DRLs. Patient data is anonymised, and each participating hospital has access to their data in a central computer server. Using DMSs may be one of the best ways to support these programs in the collection and analysis of data, raising alerts about high patient and occupational doses and suggesting optimisation actions.