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In the context of urban sustainability and the development of resilient cities, the use of 4D geospatial data and the integration and association of building information with geographical information are of considerable interest. Achieving this integration is particularly significant in the scientific field from a technical standpoint but poses significant challenges due to the incompatibility between the two environments. This research proposes various methodologies for the effective integration of BIM/GIS data by analyzing their pros and cons and highlights the innovative aspects of the integration between these systems. Starting with the use of commercial software that has enabled the integration of a building's 3D model within a GIS environment (this system is particularly useful for its ease of management and the potential for practical applications), this study progresses to an experimental virtual/augmented/mixed reality app developed by the authors that allows for the virtual integration of a building with its territorial context. It concludes with an innovative methodology that, by using the customizable and extensible libraries of the Cesium platform, facilitates the integration of structural data within a 4D geospatial space. This study demonstrates the feasibility of integrating BIM and GIS data despite inherent incompatibilities. The innovative use of Cesium platform libraries further enhances this integration, providing a comprehensive solution for intelligent and sustainable urban planning. By addressing the challenges of incompatibility, the final solution offers critical insights for a deeper understanding of evolving urban landscapes and for monitoring urban expansion and its environmental impacts. [ABSTRACT FROM AUTHOR]

Computed tomography (CT), magnetic resonance imaging (MRI), and radiography expose patients to electromagnetic fields (EMFs) and ionizing radiation. As an alternative, Electrical Impedance Tomography (EIT) offers a less EMF-influenced method for imaging by measuring superficial skin currents to provide a map of the body's conductivity. EIT allows for functional monitoring of anatomical regions using low electromagnetic fields and minimal exposure times. This paper investigates the application of EIT for the morphological and functional assessment of tissues. Using the Finite Element Method (FEM) (Comsol 5.2), both two-dimensional and three-dimensional models and simulations of physiological and pathological tissues were developed to replicate EIT operations. The primary objective is to detect carcinoma by analysing the electrical impedance response to externally applied excitations. An eight-electrode tomograph was utilised for this purpose, specifically targeting epithelial tissue. The study allowed the characterisation of tomographs of any size and, therefore, the possibility to verify both their geometric profile and the ideal value of the excitation current to be delivered per second of the type of tissue to be analysed. Simulations were conducted to observe electrical impedance variations within a homogeneously modelled tissue and a carcinoma characterized by regular geometry. The outcomes demonstrated the potential of EIT as a viable technique for carcinoma detection, emphasizing its utility in medical diagnostics with reduced EMF exposure. [ABSTRACT FROM AUTHOR]

Non-destructive testing (NDT) techniques are crucial in making informed decisions about reconstructing or repairing building structures. The SonReb method, a combination of the rebound hammer (RH) and the ultrasonic pulse velocity (UPV) tests, is widely used for this purpose. To evaluate the compressive strength, C S , of the concrete under investigation, the ultrasonic pulse velocity V p and the rebound index R must be mapped to the compressive strength C S using a suitable conversion model, the identification of which requires supplementing the NDT measurements with destructive-type measurements (DT) on a relatively large number of concrete cores. An approach notably indicated in all cases where the minimization of the number of cores is essential is to employ a pre-existing conversion model, i.e., a model derived from previous studies conducted in the literature, which must be appropriately calibrated. In this paper, we investigate the performance of Gaussian process regression (GPR) in calibrating the pre-existing SonReb conversion models, exploiting their ability to handle nonlinearity and uncertainties. The numerical results obtained using experimental data collected from the literature show that GPR calibration is very effective, outperforming, in most cases, the standard multiplicative and additive techniques used to calibrate the SonReb models. [ABSTRACT FROM AUTHOR]

The heuristic homogenization approach is intensively employed to characterize electromagnetic metamaterials (MMs). The effective parameters are extracted within this framework using the Nicolson–Ross–Weir (NRW) method. Special attention must be devoted to handling this procedure because of the branch ambiguity issue affecting it, i.e., the lack of uniqueness in the evaluation of the effective refractive index n e f f rooted in the use of the multivalued complex logarithm to invert the Airy–Fresnel relation. Over the years, several techniques based on the phase-unwrapping approach have been introduced, but without any theoretical justification. In this paper, we aim to clarify the theoretical connection between the phase unwrapping method and the analytic continuation theory framework. Furthermore, three-phase-unwrapping approaches, which descend directly from the theory we discussed, are compared to identify which approach is best suited to reconstruct the complex refractive index of metamaterials when the NRW method is applicable. [ABSTRACT FROM AUTHOR]

The Electronic Health Record (EHR) is a system for collecting and storing patient medical records as data that can be mechanically accessed, hence facilitating and assisting the medical decision-making process. EHRs exist in several formats, and each format lists thousands of keywords to classify patients data. The keywords are specific and are medical jargon; hence, data classification is very accurate. As the keywords constituting the formats of medical records express concepts by means of specific jargon without definitions or references, their proper use is left to clinicians and could be affected by their background, hence the interpretation of data could become slow or less accurate than that desired. This article presents an approach that accurately relates data in EHRs to ontologies in the medical realm. Thanks to ontologies, clinicians can be assisted when writing or analysing health records, e.g., our solution promptly suggests rigorous definitions for scientific terms, and automatically connects data spread over several parts of EHRs. The first step of our approach consists of converting selected data and keywords from several EHR formats into a format easier to parse, then the second step is merging the extracted data with specialised medical ontologies. Finally, enriched versions of the medical data are made available to professionals. The proposed approach was validated by taking samples of medical records and ontologies in the real world. The results have shown both versatility on handling data, precision of query results, and appropriate suggestions for relations among medical records. [ABSTRACT FROM AUTHOR]

Electromagnetic metamaterials (MMs) are artificial composites that exhibit exceptional physical characteristics. Their design, which relies on the retrieving of the effective medium parameters, is usually a very time-consuming process because of the high number of full-wave simulations involved in this task. To alleviate the related computational burden, we propose to use a Multi-fidelity Surrogate Modelling (MFSM) approach. Numerical results demonstrate that this methodology turns out to be promising for a quick evaluation of the scattering parameters from which the effective constitutive parameters of a MM are retrieved, as shown by two numerical examples. [ABSTRACT FROM AUTHOR]

Production of carbon fiber reinforced polymers (i.e., one of the basic material of the modern airplanes) is an elaborate process unfree from faults and problems. Errors during the manufacturing or the plies' overlapping, in fact, can cause particular flaws in the resulting material, so compromising its same integrity. Within this framework, ultrasonic tests could be useful to characterize the presence of defect, depending on its dimensions. On the contrary, the requirement of a perfect state for used polymers is unavoidable in order to assure both transport reliability and passenger safety. Therefore, a real-time approach able to recognize and classify the defect starting from the measured ultrasonic echoes could be very useful in industrial applications. The ill-posedness of the so defined process induce a regularization method. In this paper, an heuristic approach is proposed for this aim. Particularly, the proposed method is based on the use of support vector machines. Obtained results assure good performances of the implemented classifier, with very interesting applications. [ABSTRACT FROM AUTHOR]

Presents a study that developed a method for detecting and classifying defects in metallic plates. Background on nondestructive testing in the field of defect identification; Analysis of fuzzy entropy in measuring the depth of defects; Results and implications.

The evaluation of the cutoff wavenumbers of metallic waveguides can be related to the numerical resolution of a suitable nonlinear eigenproblem defined on the domain C described by the contour of its transverse cross section. In this work, we show that the symmetries of C can be exploited to obtain a block diagonal matrix representation of the nonlinear eigenproblem, which enables a remarkable reduction in the computational effort involved in its resolution. [ABSTRACT FROM AUTHOR]

During a flight, the steel plate attack wing–fuselage of an aircraft is subjected to cyclical thermal stress caused by flight altitude variation that could compromise the functionality of the plate. Thus, it is compulsory after a sequence of flights to evaluate the state of plate health. In this work, we propose a new dynamic model on the basis of the physical transmission of heat by conduction governed by a second-order parabolic partial differential equation with suitable initial and boundary conditions to analyze and forecast thermal stresses in the plate of a P64 OSCAR B airplane. Developing this model in the COMSOL Multi-Physics® environment, a finite-element technique was applied to achieve the thermal-stress map on the plate. The achieved results, equivalent to those obtained by a campaign of infrared thermographic experiment measurements (not yet used in the aeronautical industry), highlight the evolution of the thermal load of the steel plate attack wing–fuselage, adding evidence of possible incoming fatigue phenomena to identify in advance if the steel plate must be replaced. [ABSTRACT FROM AUTHOR]