Acta IMEKO

Military archaeology and LIDAR data visualizations: a non-invasive approach to detect historical remains

Joel Aldrighettoni, Maria Grazia D'Urso — Thu, 04 May 2023 00:00:00 +0000

The present paper belongs to a line of research known as aerial archaeology and compares some specific visualizations of LIDAR data (hill-shading, openness, and sky view factor) to understand which of them can provide the best approach to suitably identify and unveil some archaeological permanences as function of different boundary conditions. In the present case, such permanences belong to the very special material heritage consisting of the "physical traces" of the Great War, although latent, they persist in the present landscapes at different states of preservation and visibility, waiting to be unearthed to express their cultural potential. They represent an indispensable palimpsest of "minor signs" such as, for example, fragments of entrenchments, gun emplacements, shelters, bomb craters, and temporary shelters. Such elements made the war machine work at that time while, nowadays, if properly recognized and enhanced, could foster the historical and cultural revitalization of the territories where they are placed.

Sample volume length and registration accuracy assessment in quality controls of PW Doppler diagnostic systems: a comparative study

Thu, 04 May 2023 00:00:00 +0000

In clinical diagnostics, Pulsed Wave (PW) Doppler is one of the most used spectral Doppler techniques since it provides quantitative information about the severity of several cardiac disorders. Therefore, routine quality control tests should be scheduled to check whether a proper level of performance is maintained over time. Despite continuous research in the field, performance evaluation of Doppler equipment is still an open issue. Therefore, the present study is focused on the comparative investigation based on a test parameter for the automatic analysis of faults in sample volume length and range gate registration accuracy. The Velocity Profile Discrepancy Index (VPDI) provides a quantitative estimation according to the agreement between the theoretical parabolic velocity profile and the measured one. The index was assessed through an automatic method that post-processes PW spectrogram images acquired at six sample volume depths with respect to the vessel radius of a Doppler reference device. Tests were repeated for three brand-new ultrasound diagnostic systems, equipped with convex and phased array probes, in two working conditions. From the analysis of the results, a lower discrepancy between the measured and the theoretical velocity profile was found for the convex array probes as well as a lower uncertainty contribution.

Predicting and monitoring blood glucose through nutritional factors in type 1 diabetes by artificial neural networks

Thu, 04 May 2023 00:00:00 +0000

The monitoring and management of Postprandial Glucose Response (PGR), by administering an insulin bolus before meals, is a crucial issue in Type 1 Diabetes (T1D) patients. Artificial Pancreas (AP), which combines autonomous insulin delivery and blood glucose sensor, is a promising solution; nevertheless, it still requires input from patients about meal carbohydrate intake for bolus administration. This is due to the limited knowledge of the factors that influence PGR. Even though meal carbohydrates are regarded as the major factor influencing PGR, medical experience suggests that other nutritional should be considered. To address this issue, in this work, we propose a Machine Learning (ML)-based approach for a more comprehensive analysis of the impact of nutritional factors (i.e., carbohydrates, protein, lipids, fiber, and energy intake) on the blood glucose levels (BGLs). In particular, the proposed ML-model takes into account BGLs, insulin doses, and nutritional factors in T1D patients to predict BGLs in 60-minute time windows after a meal. A Feed-Forward Neural Network was fed with different combinations of BGLs, insulin, and nutritional factors, providing a predicted glycaemia curve as output. The validity of the proposed system was demonstrated through tests on public data and on self-produced data, adopting intra- and inter-subject approach. Results anticipate that patient-specific data about nutritional factors of a meal have a major role in the prediction of postprandial BGLs.

The role of metrology in the cyber-security of embedded devices

Pasquale Arpaia, Francesco Caputo, Antonella Cioffi, Antonio Esposito — Thu, 04 May 2023 00:00:00 +0000

The cyber-security of an embedded device is a crucial issue especially in the Internet of Things (IoT) paradigm, since the physical accessibility to the smart transducers eases an attacker to eavesdrop the exchanged messages. In this manuscript, the role of metrology in improving the characterization and security testing of embedded devices is discussed in terms of vulnerability testing and robustness evaluation. The presented methods ensure an accurate assessment of the device’s security by relying on statistical analysis and design of experiments. A particular focus is given on power analysis by means of a scatter attack. In this context, the metrological approach contributes to guaranteeing the confidentiality and integrity of the data exchanged by IoT transducers.

Electroencephalography correlates of fear of heights in a virtual reality environment

Thu, 04 May 2023 00:00:00 +0000

An electroencephalography (EEG)-based classification system of three levels of fear of heights is proposed. A virtual reality (VR) scenario representing a canyon was exploited to gradually expose the subjects to fear inducing stimuli with increasing intensity. An elevating platform allowed the subjects to reach three different height levels. Psychometric tools were employed to initially assess the severity of fear of heights and to assess the effectiveness of fear induction. A feasibility study was conducted on eight subjects who underwent three experimental sessions. The EEG signals were acquired through a 32-channel headset during the exposure to the eliciting VR scenario. The main EEG bands and scalp regions were explored in order to identify which are the most affected by the fear of heights. As a result, the gamma band, followed by the high-beta band, and the frontal area of the scalp resulted the most significant. The average accuracies in the within-subject case for the three-classes fear classification task, were computed. The frontal region of the scalp resulted particularly relevant and an average accuracy of (68.20 ± 11.60) % was achieved using as features the absolute powers in the five EEG bands. Considering the frontal region only, the most significant EEG bands resulted to be the high-beta and gamma bands achieving accuracies of (57.90 ± 10.10) % and of (61.30 ± 8.43) %, respectively. The Sequential Feature Selection (SFS) confirmed those results by selecting for the whole set of channels, in the 48.26 % of the cases the gamma band and in the 22.92 % the high-beta band and by achieving an average accuracy of (86.10 ± 8.29) %.

Electroencephalographic-based wearable instrumentation to monitor the executive functions during gait: a feasibility study

Fri, 05 May 2023 00:00:00 +0000

A feasibility study on electroencephalographic monitoring of executive functions during dual (motor and cognitive) task execution is presented. Electroencephalographic (EEG) signals are acquired by means of a wearable device with few channels and dry electrodes. The light weight and wireless device allow for walking in a natural way. The most significant EEG features are investigated to classify different levels of activation for two fundamental Executive Functions (EF) both in sitting and walking conditions. Power spectral density in the gamma band resulted in the most relevant feature in discriminating low and high levels of Inhibition. Power spectral density in the beta and gamma bands resulted the most discriminating the level of activation of Working Memory. The study poses the basis for (i) monitoring the activation levels of EF during Gait allowing loss prevention in the elderly and (ii) specific cognitive rehabilitation aimed at the most relevant executive functions during walking.

On the suitability of redundant accelerometers for the implementation of smart oscillation monitoring system: Preliminary assessment

Giorgio de Alteriis, Enzo Caputo, Rosario Schiano Lo Moriello — Mon, 15 May 2023 00:00:00 +0000

Structural health monitoring (SHM) is an essential aspect to ensure the safety and longevity of civil infrastructure. In recent years, there has been a growing interest in developing SHM systems based on Micro-Electro-Mechanical Systems (MEMS) technology. MEMS-based sensors are small, low-power, and cost-effective, making them ideal for large-scale deployment in structural monitoring systems. However, the use of MEMS-based sensors in SHM systems can be challenging due to their inherent errors, such as drift, noise, and bias instability; these errors can affect the accuracy and reliability of the measured data, leading to false alarms or missed detections. Therefore, several methods have been proposed to compensate for these errors and improve the performance of MEMS-based SHM systems. For this purpose, the authors propose the combined of a redundant configuration of cost-effective MEMS accelerometers and a Kalman Filter approach to compensate MEMS inertial sensor errors and data filtering; the performance of the method is preliminarily assessed by means of a custom-controlled oscillation generator and compared with that granted by a high-cost, high-performance MEMS reference system where amplitude differences of 0.02 m/s² have been experienced. Finally, a sensor node for real-time monitoring has been proposed that exploits LoRaWAN and NFC protocols to access the structure information to be monitored.

Probability theory as a logic for modelling the measurement process

Giovanni Battista Rossi, Francesco Crenna, Marta Berardengo — Tue, 16 May 2023 00:00:00 +0000

The problem of the nature of probability has been drawn to the attention of the measurement community in the comparison between the frequentist and the Bayesian views, in the expression and the evaluation of measurement uncertainty. In this regard, it is here suggested that probability can be interpreted as a logic for developing models of measurement capable of accounting for uncertainty. This contributes to regard measurement theory as an autonomous discipline, rather than a mere application field for statistics. Following a previous work in this line of research, where only measurement representations, through the various kinds of scales, were considered, here the modelling of the measurement process is discussed and the validity of the approach is confirmed, which suggests that the vision of probability as a logic could be adopted for the entire measurement theory. With this approach, a deterministic model can be turned into probabilistic by simply shifting from a deterministic to a probabilistic semantic.

Effects of saliva on additive manufacturing materials for dentistry applications: Experimental research using flexural strength analysis

Wed, 31 May 2023 00:00:00 +0000

Accurate and reliable results in orthodontics heavily depend on selecting the right impression materials. With the rise of digital technology and additive manufacturing techniques, it has become necessary to characterize experimentally the materials used to design prosthetic bases. In this study, the mechanical properties of Polyetheretherketone, Nylon6, Nylon12, and Polypropylene are analyzed, as impression materials commonly used in dentistry applications. Specifically, the effect on their flexural elastic modulus of the exposure to working environment conditions is also investigated by means of 3-point bending test performed on virgin materials and samples immersed in saliva for 72 hours. The proposed approach revealed significant behavior in terms of loss in mechanical performances. These findings have significant implications for the proper selection and use of AM materials in dental applications.

Image analysis for the sorting of brick and masonry waste using machine learning methods

Elske Linß, Jurij Walz, Carsten Könke — Thu, 01 Jun 2023 00:00:00 +0000

This paper describes different machine learning methods for recognizing and distinguishing brick types in masonry debris. Certain types of bricks, such as roof tiles, facing bricks and vertically perforated bricks can be reused and recycled in different ways if it is possible to separate them by optical sorting. The aim of the research was to test different classification methods from machine learning for this task based on high-resolution images. For this purpose, image captures of different bricks were made with an image acquisition system, the data was pre-processed, segmented, significant features selected and different AI methods were applied. A support vector machine (SVM), multilayer perceptron (MLP), and k-nearest neighbor (k-NN) classifier were used to classify the images. As a result, a recognition rate of 98 % and higher was achieved for the classification into the three investigated brick classes

Metrology in the early days of Social Sciences

Clara Monteiro Vieira, Elisabeth Costa Monteiro — Wed, 31 May 2023 00:00:00 +0000

Recent studies have been endeavoring to overcome challenges to ensure reliable measurement results in Social Sciences and Humanities facing the complex characteristics of this scientific field. However, the literature indicates that the founding designers of sociology as an academic discipline expressed concerns regarding social measurements more than a century ago. Based on a literature review, the present work investigates possible metrological aspects already addressed in the early days of Social Science, focusing on the methodological conceptions of two of sociology’s early canons – notably Max Weber and Emile Durkheim. The present study reveals that the approaches contemporaneously developed by the two Social Sciences co-founders present diverse but fundamentally complementary configurations, allowing a wide range of social phenomena to be analyzable. Although employing their terminologies, both social scientists incorporated fundamental metrological concepts in their procedures’ parameters, seeking to establish a single reference, using statistical analysis or determining measurement standards that resemble what is known today as reference material. The concern with applying metrological concepts since the early days of creating sociology as a science reinforces the need to invest extensive efforts to provide uniformity of measurements in this remarkably relevant field of application of Measurement Science.

The results of atmospheric parameters measurements in the millimeter wavelength range on the radio astronomy observatory “Suffa Plateau”

Dilshod Raupov, S. Ilyasov, G. I. Shanin — Tue, 06 Jun 2023 00:00:00 +0000

The results of measurements of atmospheric absorption and the amount of precipitated water on the Suffa Plateau for the period from January, 2015 to November, 2020, are presented. The measurements of atmospheric parameters in the 2 and 3 mm range of the radio waves spectrum were carried out using the MIAP-2 radiometer. The results of more than six years of measurements have show that on the Suffa Plateau, atmospheric parameters in the above range remain fairly stable. The median value of the atmospheric absorption and the amount of precipitated water over the entire observation period were 0.14 and 0.12 Nep and 5.91 and 9.83 mm, respectively, for the ranges of 2 and 3 mm.

Results of study of quantization and discretization error of digital tachometers with encoder

Vasyl Kukharchuk, Oleksandr Vasilevskyi, Volodymyr Holodiuk — Tue, 06 Jun 2023 00:00:00 +0000

The analysis of measuring channels of angular velocity with an encoder given by the authors made it possible for the first time to obtain an equation for estimating the quantization and sampling error for an exponential mathematical model describing the transient process of operation of electrical machines. The components of the mathematical model of this dynamic error are the sampling step and the derivative, which characterizes the rate of change of the measured value over time. It was found that the errors of quantization and sampling significantly depend on the value of the resolution z of the encoder. Moreover, an increase in z leads to a decrease in the sampling error, but the relative quantization error increases. To reconcile these components of errors, the laws of change in the distinguishing ability z of the encoder are adaptive to the dynamic properties of the change in angular velocity over time.

Proved that to ensure the maximum speed of measuring the angular velocity during the transient process, it is advisable to implement the method of changing the distinguishing ability of the encoder on the internal timers of the microcontroller proposed adaptive to its dynamic properties, and the quantization of informative periods proportional to the measured angular velocity should be carried out in "adjoining intervals".

Case studies for the MATHMET Quality Management System at VSL, the Dutch National Metrology Institute

Gertjan Kok — Wed, 07 Jun 2023 00:00:00 +0000

The European Metrology Network MATHMET is a network in which a large number of European national metrology institutes combine their forces in the area of mathematics and statistics applied to metrological problems. One underlying principle of such a cooperation is to have a common understanding of the ‘quality’ of software, data and guidelines. To this purpose a flexible, lightweight Quality Management System (QMS), also referred to as Quality Assessment Tools (QAT), is under development by the EMN. In this contribution the application of the QMS to several use cases of different nature by VSL is presented. The benefits and usefulness of the current version of the QMS are discussed from the particular viewpoint of a particular employee of VSL, and an outlook for possible future extensions and usage of the QMS is given.

Mathmet Measurement Uncertainty Training activity – Overview of courses, software, and classroom examples

Francesca Pennecchi, Peter Harris — Mon, 22 May 2023 00:00:00 +0000

A collaborative activity on “Measurement Uncertainty (MU) Training” under the auspices of the European Metrology Network for Mathematics and Statistics (Mathmet) is underway. This abstract reports on the progress to undertake surveys of existing training courses on MU, software for MU evaluation, and classroom examples to support the understanding of methods for MU evaluation. An appreciable number of training courses, software and examples have been identified and are currently under review. These tools and materials will be analysed and categorised according to their main features and characteristics. Special attention will be given to their adherence to the JCGM guidelines (i.e., JCGM 100:2008, JCGM 101:2008 and JCGM 102:2011). It is hoped that the knowledge assembled in this activity will help practitioners to make good choices about appropriate material to support their training needs, as well as help developers of training material to ensure good coverage of their training products and target them at user needs.