Search Results (461)

Precise online measurement of large structural components is urgently needed in modern manufacturing and intelligent construction, requiring a measurement range over 1 m, near-millimeter accuracy, second-level measurement speed, and adaptability to complex environments. In this paper, three mainstream measurement technologies, namely the image method, line laser scanning method, and structured light method, are comparatively analyzed. The structured light method exhibits remarkable comprehensive advantages in terms of accuracy and speed; however, it suffers from the issue of occlusion during contour measurement. To tackle this problem, multi-camera stitching is employed, wherein the accuracy of camera calibration plays a crucial role in determining the quality of point cloud stitching. Focusing on the cable tightening scenario of meter-diameter cables in cable-stayed bridges, this study develops a contour measurement system based on the collaboration of multiple structured light cameras. Measurement indicators are optimized through modeling analysis, system construction, and performance verification. During verification, four structured light scanners were adopted, and measurements were repeated 11 times for the test workpieces. Experimental results demonstrate that although the current measurement errors have not yet been stably controlled within the millimeter level, this research provides technical exploration and practical experience for high-precision measurement in the field of intelligent construction, thus laying a solid foundation for subsequent accuracy improvement. Full article

In today’s digital ecosystem, where millions of users interact with diverse online services and generate vast amounts of textual, transactional, and behavioral data, ensuring the trustworthiness of this information has become a critical challenge. Low-quality data—manifesting as incompleteness, inconsistency, duplication, or noise—not only undermines analytics and machine learning models but also exposes unsuspecting users to unreliable services, compromised authentication mechanisms, and biased decision-making processes. Traditional data quality assessment methods, largely based on manual inspection or rigid rule-based validation, cannot cope with the scale, heterogeneity, and velocity of modern data streams. To address this gap, we propose DQMAF (Data Quality Modeling and Assessment Framework), a generalized machine learning–driven approach that systematically profiles, evaluates, and classifies data quality to protect end-users and enhance the reliability of Internet services. DQMAF introduces an automated profiling mechanism that measures multiple dimensions of data quality—completeness, consistency, accuracy, and structural conformity—and aggregates them into interpretable quality scores. Records are then categorized into high, medium, and low quality, enabling downstream systems to filter or adapt their behavior accordingly. A distinctive strength of DQMAF lies in integrating profiling with supervised machine learning models, producing scalable and reusable quality assessments applicable across domains such as social media, healthcare, IoT, and e-commerce. The framework incorporates modular preprocessing, feature engineering, and classification components using Decision Trees, Random Forest, XGBoost, AdaBoost, and CatBoost to balance performance and interpretability. We validate DQMAF on a publicly available Airbnb dataset, showing its effectiveness in detecting and classifying data issues with high accuracy. The results highlight its scalability and adaptability for real-world big data pipelines, supporting user protection, document and text-based classification, and proactive data governance while improving trust in analytics and AI-driven applications. Full article

Background/Objective: Clinical handover of patient information is a key component of patient care in hospitals. Nurses use a structured framework to minimise communication errors. Electronic Medical Record (EMR) systems can support patient safety and clinical handover with contemporaneous documentation. The aim of this study was to evaluate nurses’ adoption, perceived usability, and satisfaction with an updated handover page within the EMR. Methods: A pre-post mixed-methods study across a large Australian tertiary healthcare organisation examined handover page adoption using data from the EMR, and perceived usability and satisfaction were measured using a survey (handover page updated in EMR on 23 September 2024). Descriptive and inferential statistical analyses were conducted for quantitative data, and content analysis was used for qualitative data. Results: Adoption of the handover page was not statistically significant post-update (Wilcoxon signed-rank test z = −1.376, p = 0.169). Improved usability of the updated handover page post-update was demonstrated by a statistically significant decrease in the need to navigate away from the page to find relevant clinical information during handover (Fisher’s Exact Test p = 0.042). Nurses’ satisfaction increased, indicated by statistically significant increases in two items of the End User Computing Satisfaction Scale (precise information (Mann–Whitney U = 963.50, p = 0.040); and sufficient information (Mann–Whitney U = 927.50, p = 0.034)). Free-text comments indicated adoption and acceptability of the updated handover page by nurses, although a gap remains in the practice process. Conclusions: A co-designed solution to update the handover page within the EMR had good usability and satisfaction among nurses. Updates or implementations to digital health technologies must be continuously evaluated by specialist informatics teams to ensure appropriate adoption, usability and satisfaction by nurses, and positive repercussions for patient safety. Full article

As is well known, intelligence and efficiency are important development directions for modern agriculture. The harvesting header, as key components of crop harvesters, have significant implications for achieving intelligent control of their working height, which has a notable impact on reducing harvest loss. To understand the current state of intelligent control technology for the working height of a crop harvesting header, and to explore their application potential, this article provides a relatively systematic literature review. Firstly, we analyzed the structure and principle of the harvesting header of typical grain and oil crops such as rice and peanuts. Secondly, we briefly described the current methods for controlling the working height of the harvesting header. They mainly use two methods: mechanical profiling and electro-hydraulic profiling. Thirdly, we focused on researching and analyzing the measurement methods and control algorithms for the working height of the harvesting header. Finally, we pointed out the problems in the current height control of the harvesting header. These problems mainly include insufficient measurement accuracy of working height in complex terrain, slow response and large delay of working height hydraulic control system, incompatibility between working height control models and strategies, and relatively single working height measurement methods. Full article

Aluminium plays a key role in developing modern energy technologies, from electrical systems to high-energy materials, providing a combination of functionality, economy, and reliability, but the oxide film on its particles reduces the effective reactivity. This work aims to increase the reactivity of aluminum powder by mechanochemical treatment using modifiers. The materials used were aluminum powder of the ASD brand and graphite of the GL-1 brand. The experiment subjected aluminum powder to mechanochemical treatment (MCT) with different graphite contents. It was shown that MCT significantly increases active aluminum content in the powder due to partial destruction of the oxide film on its surface. In addition, morphological analyses confirm the destruction of the oxide, the graphite coating, and the appearance of lamellar structures measuring 0–58 µm. Thermal analysis shows that the primary exothermic peak shifts from 662.6 °C to 653.9 °C for Al + 10% graphite, and the heat released increases by 27%, which means lower activation energy and more complete oxidation. However, at 20% graphite, the thermal gain decreases, since carbon shields the metal areas. Thus, the optimal content is 10% graphite: at this ratio, the best thermochemical behavior of the powder is achieved. The data obtained indicate that the MCT of aluminum powder with graphite effectively increases its reactivity. The resulting aluminum powders with modified particle surfaces facilitate the development of new technologies for the creation of various high-energy solid propellant systems. For rocket engines, preference is given to solid rocket propellant (SRP), which is a mixture of substances (components) capable of burning in the absence of air, producing a large amount of gaseous working fluid heated to a high temperature, providing thrust. Full article

Reverse arch beam string-inclined column structures have been applied in large-scale event venues due to their unique load-bearing characteristics. However, ensuring their resistance to progressive collapse remains a critical challenge. To investigate the structural robustness of reverse arch beam string-inclined column structure in practical engineering applications, a simplified finite element model is developed herein using ANSYS APDL. The natural frequencies of the actual engineering structure are measured through the hammering method to validate the accuracy of the simulation model. Based on the component removal method, different structural components are removed and finite element analysis is carried out. The dynamic response of the overall structure and the importance coefficients of individual components after removal are examined. The results demonstrate good agreement between the natural frequencies measured by the impact hammer test and those predicted by the finite element simulations, with the difference being only 1.67%. It is found that upper beam failure is fatal to this structure; the outer inclined columns significantly affect the robustness of the structure, while the failure of a single strut has a negligible impact. According to the component division, the importance of the overall robustness of the structure is in the following order: upper beam > column end > column base > strut. The maximum stress is mostly located in beam 7, beam 8, beam 28, and beam 107, which needs to be focused on. Full article

The paper presents a method for obtaining partially degradable capillary membranes from a polyethersulfone/polycaprolactone (PES/PCL) mixture. PES/PCL membranes were obtained by the phase inversion technique with dry/wet spinning and then subjected to controlled degradation in an alkaline environment (1 M NaOH) and simulated body fluid (SBF with pH 7.4) using the flow method. The aim of the work was to select and apply a degradable, non-toxic, simple polymer as a removable component of the membrane structure. The degradable component of the membranes was PCL, the gradual hydrolysis of which was aimed at increasing the porosity and improving the transport properties of the membranes during operation. The membrane properties, such as hydraulic permeability coefficient (UFC), retention coefficient, and structural morphology, were assessed using scanning electron microscopy (SEM) before and after degradation. Analysis of SEM images performed with MeMoExplorer^TM software showed an increase in the proportion of large pores (above 300 µm²) and total porosity of the membranes after degradation in NaOH and SBF. Low instability factor (<0.25) for all samples, both before and after degradation, confirms the good repeatability of the membrane structure. An increase in the UFC was observed, while the retention coefficients did not change significantly in the case of membranes after the etching process. The degradation of the PCL component in the membrane was assessed using the weight method. Measurements of the membrane mass loss before and after degradation confirmed the removal of over 50 wt.% of the PCL component in SBF and 70 wt.% in NaOH from the tested membranes, which resulted in an increase in permeability due to increased membrane porosity. The results indicate the possibility of using such structures as functional, partially self-regulating membranes, potentially useful in biomedical and environmental applications. Full article

This paper presents a BIM-oriented methodological framework for integrating air quality monitoring systems based on IoT sensors into building and infrastructure projects. A set of low-cost environmental sensors capable of measuring PM1, PM2.5, PM10, temperature, and humidity was deployed in a real residential setting to illustrate the proposed approach. To enable semantic integration within BIM workflows, a structured classification system, AllBIMclass, was developed. It provides dedicated hierarchical codes for environmental sensors, defined by monitored parameters, installation location (indoor, outdoor, or mixed), power supply, and data handling mode. The pilot experience demonstrated how sensors can be registered, classified, and linked to BIM models, supporting data visualisation and basic management tasks. AllBIMclass is available in Revit 2026 (version 26.6.4.409, build 20250227_1515, 64-bit) (TXT) and Archicad 28 (version 28.0.0, build 3001, x86–64-bit) (XML) formats and is fully compatible with IFC schemas. Although the framework has not yet been applied to large-scale projects, its components are technically operational and ready for implementation. This research contributes to bridging the gap between environmental monitoring and digital construction workflows, paving the way for integration into digital twins, smart buildings, and sustainable infrastructure systems. Full article

Critical Infrastructures (CIs) are the backbone of modern societies, providing essential services whose disruption can have severe consequences. The interdependencies among the CIs, across sectors and national borders, add significant complexity to risk and resilience management. While various EU Directives and EU-funded projects have addressed CI risk management, most efforts have focused on individual infrastructures rather than systemic cross-sector and cross-border approaches. In the EU-funded project ATLANTIS, we address this gap by advancing CI risk and resilience assessment towards a fully integrated European protection framework. We emphasise a holistic, multi-level approach that transcends individual assets, enabling coordination across operators, sectors, and national borders. To this end, we introduce a comprehensive risk assessment methodology that explicitly accounts for interdependencies among CIs and evaluates potential impacts and probabilities of disruptive events. This methodology is underpinned by the tailored data management framework, structured across three integrated layers. To validate the approach, novel tools and methods were implemented and tested in three large-scale pilot exercises, conducted through a series of stakeholder workshops. Results indicated measurable improvements in CI preparedness and awareness, ranging from approximately 5% to 55%, depending on the threat scenario and stakeholder group. The findings demonstrate that our approach delivers added value by supporting enhanced decision-making and fostering consistent, cross-CI communication through a shared platform. This paper presents the key components, cross-CI and multi-threat risk assessment methodology, and testing outcomes of the ATLANTIS project, highlighting its contribution to advancing European CI resilience. Full article

Smartphone-based strain monitoring of structural components is an emerging approach to structural health monitoring. However, the existing techniques suffer from limited accuracy and poor cross-device adaptability. This study aims to optimize the smartphone-based Micro Image Strain Sensing (MISS) method by replacing the traditional Connected Component Labeling (CCL) algorithm with the arc-support line segments (ASLS) algorithm, thereby significantly enhancing the stability and adaptability of circle detection in micro-images captured by diverse smartphones. Additionally, this study evaluates the impact of lighting conditions and lens distortion on the optimized MISS method. The experimental results demonstrate that the ASLS algorithm outperforms CCL in terms of recognition accuracy (maximum error of 0.94%) and cross-device adaptability, exhibiting greater robustness against color temperature and focal length variations. Under fluctuating lighting conditions, the strain measurement noise remains within ±0.5 με and with a maximum error of 7.0 με compared to LVDT measurements, indicating the strong adaptability of the optimized MISS method to external light changes. Barrel distortion in microscopic images induces a maximum pixel error of 5.66%, yet the final optimized MISS method achieves highly accurate strain measurements. The optimized MISS method significantly improves measurement stability and engineering applicability, enabling effective large-scale implementation for strain monitoring of civil infrastructure. Full article

Background/Objectives: Maternal vitamin supplementation (including folic acid, vitamin D, and multivitamin supplements) during pregnancy may lower the likelihood of neurodevelopmental disorders in offspring. This study examines the associations between maternal vitamin suppletion during pregnancy and morphological patterns in offsprings’ brain structure and traits of Autism Spectrum Disorder (ASD) and Attention-Deficit Hyperactivity Disorder (ADHD) in a large population-based study of child development. Methods: The study cohort included a total of 3937 children (aged 9–11) participating in the Generation R cohort in Rotterdam, the Netherlands. Maternal vitamin D and folateserum levels, multivitamin supplement use, and overall dietary quality (as assessed by the Food Frequency Questionnaire, FFQ) during pregnancy were used as predictors. T1 structural MRI scans were acquired and segmented using Freesurfer to assess brain morphometry. Cortical and subcortical brain volumes of children were separated into four independent components and used as mediators. ADHD and ASD traits, as measured by parent-completed questionnaires (Child Behavior CheckList and Social Responsiveness Scale, respectively) were used as outcome variables. Results: Results show that (1) maternal vitamin D, multivitamin supplementation, and better diet quality were associated with fewer ADHD or ASD traits in the offspring; (2) vitamin D and diet quality were associated with larger-volume childhood brain components; (3) larger-volume brain components were associated with fewer ADHD and ASD traits; (4) part of the association between dietary factors in pregnancy and offspring ADHD and ASD traits was mediated through the brain volumes of the children. Conclusions: Though all observed effect sizes were small, further population-based research should be performed to further delineate the effects of gestational multivitamin and vitamin D exposure and investigate whether this may be an avenue for preventive interventions. Full article

Large-scale, high-density flatness measurement is critical for manufacturing reference surfaces in ultra-precision machine tools. Traditional methods exhibit degradation in both accuracy and efficiency as measurement points and area size increase. In order to overcome these limitations to meet the requirements for integrated in-process measurement and machining of structural components in ultra-precision machine tools, this paper proposes a novel nine-probe third-order matrix system that integrates the Fine Sequential Three-Point (FSTRP) method with automated scanning path planning. The system utilizes a multi-probe error separation algorithm based on the FSTRP principle, combined with real-time adaptive sampling, to decouple machine tool motion errors from intrinsic workpiece flatness deviations. This system breaks through traditional multi-probe 1D straightness measurement limitations, enabling direct 2D flatness measurement (with X/Y error decoupling), higher sampling density, and a repeatability standard deviation of 0.32 μm for large precision machine tool components. This high-efficiency, high-precision solution is particularly suitable for automated flatness inspection of large-scale components, providing a reliable metrology solution for integrated measurement-machining of flatness on precision machine tool critical components. Full article

This article addresses the state of the art of methodologies for bridge inspection with potential for inclusion in Bridge Management Systems (BMS) and within the scope of the IABSE Task Group 5.9 on Remote Inspection of Bridges. The document covers computer vision approaches, including 3D geometric reconstitution (photogrammetry, LiDAR, and hybrid fusion strategies), damage and component identification (based on heuristics and Artificial Intelligence), and non-contact measurement of key structural parameters (displacements, strains, and modal parameters). Additionally, it addresses techniques for handling the large volumes of data generated by bridge inspections (Big Data), the use of Digital Twins for asset maintenance, and dedicated applications of Augmented Reality based on immersive environments for bridge inspection. These methodologies will contribute to safe, automated, and intelligent assessment and maintenance of bridges, enhancing resilience and lifespan of transportation infrastructure under changing climate. Full article

In response to issues of long construction cycles, high pollution, and labor shortages in traditional cast in situ subway station construction, a refined 3D model of a large-segment prefabricated subway station was established using ABAQUS software 2024, with mechanical behavior throughout the construction process studied based on the Shenzhen Huaxia Station project case. The model incorporates a concrete inelastic damage constitutive model and a steel elastic–plastic model, accurately simulates key components, including dry joints of mortise–tenon grooves, prestressed reinforcement, and bolted connections, and implements a seven-phase construction sequence. Research findings indicate the following: (1) During component assembly, the roof vault settlement remains ≤3.8 mm, but backfilling significantly increases displacements (roof settlement reaches 45 mm, middle slab deflection measures 66.91 mm). (2) Longitudinal mortise–tenon joints develop stress concentrations due to stiffness disparities, with mid-column installation slots identified as vulnerable zones exhibiting maximum Von Mises stress of 32 MPa. (3) Mid-column eccentricity induces structural asymmetry, causing increased deflection in longer-span middle slabs, corbel contact stress differentials up to 6 MPa, and bolt tensile stresses exceeding 1.1 GPa. (4) The arched roof effectively transfers loads via three-hinged arch mechanisms, though spandrel horizontal displacement triggers 5 cm rebound in diaphragm wall displacement. Conclusions confirm overall the stability of the prefabricated structure while recommending the optimization of member stiffness matching, avoidance of asymmetric designs, and localized reinforcement for mortise–tenon edges and mid-column joints. Results provide valuable references for analogous projects. Full article

This study investigates the effects of Hot Isostatic Pressing (HIP) treatment on the microstructural evolution and mechanical properties of Laser Powder Bed Fusion (LPBF)-manufactured Hastelloy H. This research evaluates the trade-offs between defect elimination, anisotropy reduction, and strength retention in well-optimized LPBF components. Specimens were manufactured using optimized LPBF parameters, achieving 99.85% density, and then subjected to HIP treatment at 1160 °C/100 MPa for 4 h. The analysis includes porosity analysis, grain size measurement, crystallographic texture evaluation, and tensile tests in two principal orientations. The results show that HIP treatment provides minimal benefits for defect elimination in already high-quality LPBF material, reducing porosity from 0.15% to <0.01%—a negligible improvement that does not translate to proportional mechanical enhancement. Tensile tests show that as-built specimens exhibited orientation-dependent strength, with XY-oriented samples reaching a yield strength (YS) of 682 MPa, ultimate tensile strength (UTS) of 864 MPa, and elongation of 17%, while XZ-oriented samples showed lower strength (YS = 621 MPa, UTS = 653 MPa) but superior ductility (elongation = 47%). After HIP treatment, anisotropy was largely removed, with both XY and XZ orientations showing comparable strength (YS ≈ 315–317 MPa, UTS ≈ 682–691 MPa) and elongation (38–41%). This indicates that HIP significantly improves ductility and isotropy at the cost of reduced strength. HIP treatment effectively eliminates the anisotropy of LPBF components, achieving uniform hardness across all orientations while reducing crystallographic texture intensity from 12.3× to 3.2× random orientation. This isotropy improvement occurs through grain-coarsening mechanisms that increase the average grain size from 7.5 μm to 13.5 μm, eliminating cellular–dendritic strengthening structures and reducing hardness by 32% (254 HV2 to 170 HV2) following Hall–Petch relationships. The conducted research confirms that HIP treatment allows for modification of the microstructure of Hastelloy X alloy, which may lead to the improvement of its mechanical properties in high-temperature applications and a significant increase in the isotropy of the material. Full article