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Dynamic monitoring is a well-established technique used to gain information on the global health of constructions. In particular, ambient vibration tests have achieved important results in the dynamic characterization of modal parameters. Several techniques and instrumentations are currently available, however the accuracy of these results is often unquestioned. The mutual validation between different modal analysis techniques is an important procedure to assess the reliability of the results. In the present paper the ambient vibration tests performed on the so-called ‘Temple of Minerva Medica’ in Rome considering different techniques and instrumentations will be described and compared. While it is referred to as the Temple of Minerva Medica, the structure is actually a ruined decagonal nymphaeum in opus latericium that dates to the 4th century AD. Today, the construction is located between the main central train station (Roma Termini) and the local tram way. Ambient vibration data were acquired during different campaigns [1] to characterize the effects of the vibrations and the modal parameters of the structure. This work deals with the data collected on the 11th of July 2019 within the project “Tecnologie per il miglioramento della Sicurezza e la ricostruzione dei centri Storici in area sismica” coordinated by DTC Lazio (Distretto Tecnologico beni e attività culturali). The instrumentation comprised of several seismographs equipped with triaxial velocimeters and piezoelectric accelerometers. A variety of techniques were applied to process the acquired vibration data in order to extract the modal parameters of the studied structure including PolyMAX, FDD, EFDD, CC-SSI, HVSR and FRF. Comparison of the modal parameters obtained by each different technique was considered to provide indications on the reliability of the instruments.

An important task in underwater autonomous vehicle swarm management is the knowledge of the graph topology, to be obtained with the minimum possible communication exchanges and amid heavy interferences and background noises. Despite the importance of the task, this problem is still partially unsolved. Recently, the Fast Fourier Transform and the addition of white noise to consensus signals have been proposed independently to determine respectively the laplacian spectrum and the adjacency matrix of the graph of interacting agents from consensus time series, but both methodologies suffer technical difficulties. In this paper, we combine them in order to simplify calculations, save energy and avoid topological reconstruction errors using only the largest eigenvalue of the spectrum and instead of white noise, a high frequency, low amplitude noise. Numerical simulations of several swarms (random, small-world, pipeline, grid) show an exact reconstruction of the configuration topologies.

"Time series can be transformed into graphs called horizontal visibility graphs (HVGs) in order to gain useful insights. Here, the maximum eigenvalue of the adjacency matrix associated to the HVG derived from several time series is calculated. The maximum eigenvalue methodology is able to discriminate between chaos and randomness and is suitable for short time series, hence for experimental results. An application to the United States gross domestic product data is given."

The structural diagnosis of historic buildings should integrate on-site and in-the-laboratory experimental testing techniques, with no harmful effects on the structural and aesthetic health of the monument. In the present paper several nondestructive tests (NDTs) were conducted to study an archeological ruined building located in Rome, the so-called Temple of Minerva Medica. In particular, the experimental program comprised 3D geometric surveys by laser scanning and stereo-photogrammetry, thermal imaging, microclimatic parameters acquisition, sonic testing and ambient vibration monitoring. The above NDTs were executed from summer of 2016 until summer of 2017, in order to investigate the seasonal effects and/or the eventual changes in the structural response of the building, after the 2016-2017 Central Italy seismic sequence. The acquired data were stored in a repository that is available to the end-users for future studies and analyses.

A preliminary characterization of the input vibrations and of the dynamic behavior of the Sarcophagus of the Spouses at the National Etruscan Museum in Rome by advanced digital videos analyses is illustrated. This activity focuses on the development of a protection system for museum assets in order to reduce potential damage due to traffic and earthquakes. The vibrations induced by roads, tramways and an underground train line were measured by seismometers and analyzed to characterize the base excitation to the Sarcophagus. Given the high vulnerability of the Sarcophagus, no instrumentation could be placed on it, so that conventional contact sensors could not be used. Consequently, non-contact video-based techniques were considered and, in particular, high-speed and high-resolution video camera footage was recorded. The video was analyzed by advanced algorithms derived from the motion magnification method, which is a video signal elaboration method able to enormously amplify the tiniest movements of the acquired objects. A preliminary estimation of the main dynamic characteristics of the Sarcophagus was performed. The associated frequencies will be used to calibrate the numerical models and to optimize the design of the base-isolation system. The used digital video analysis technique is also discussed in terms of its many advantages and its application criticalities.

Information about the early growth of infectious outbreaks is indispensable to estimate the epidemic spreading. A large number of mathematical tools have been developed to this end, facing as much large number of different dynamic evolutions, ranging from sub-linear to super-exponential growth. Of course, the crucial point is that we do not have enough data during the initial outbreak phase to make reliable inferences. Here we propose a straightforward methodology to estimate the epidemic growth dynamic from the cumulative infected data of just a week, provided a surveillance system is available over the whole territory. The methodology, based on the Newcomb-Benford Law, is applied to the Italian covid 19 case-study. Results show that it is possible to discriminate the epidemic dynamics using the first seven data points collected in fifty Italian cities. Moreover, the most probable approximating function of the growth within a six-week epidemic scenario is identified., Complex network, Dynamical systems, Graph theory, Big data, Epidemic spreading, Infective diseases.

A new methodology for digital image processing, namely the Motion Magnification (MM), allows to magnify small displacements of large structures. MM acts like a microscope for motion in video sequences, but affecting only some groups of pixels. The processed videos unveil motions hardly visible with the naked eye and allow a more effective frequency domain analysis. We applied the MM method to several historic structures, including a 1:10-scale mockup of Hagia Irene in Constantinople tested on shaking table, the so-called Temple of Minerva Medica in Rome and the Ponte delle Torri of Spoleto. MM algorithms parameters were calibrated by comparison with reference consolidated modal identification methods applied to conventional velocimeters data. Encouraging results were obtained in terms of vibration monitoring and modal analysis for dynamic identification of the studied structures, offering a low-cost, viable support to the standard vibration sensing equipment, such as contact velocimeters, laser vibrometers and others.

The Internet of Things (IoT) is a novel paradigm based on the connectivity among different entities or “things”. IoT environment in the form of interconnected smart “things” represents a great potential in terms of effective and efficient solutions related to urban context (e.g., system architecture, design and development, human involvement, data management and applications). On the other hand, with the introduction of the IoT environment, devices and network security have become a fundamental and challenging issue. Moreover, growing number of users connected via IoT system necessitates focusing on the vulnerability of complex networks and defence challenges at the topological level. This paper addresses these challenges from the perspective of graph theory. In this work, the authors introduce a novel AV11 algorithm to identify the most critical and influential IoT nodes in a Social IoT (SIoT) network in a smart city context using ENEA Portici CRESCO infrastructure.

A new methodology for digital image processing, namely the Motion Magnification, allows to magnify small displacements of large structures. Motion magnification acts like a microscope for motion in video sequences, but affecting only some groups of pixels. The processed videos unveil motions hardly visible with the naked eye. We apply the motion magnification to a scale mockup of the Hagia Irene church stressed by a shaking table, to the so-called Temple of Minerva Medica in Rome and to the Ponte delle Torri of Spoleto. Results are surprising, offering a low-cost, viable support to the standard equipment such as contact accelerometers, laser vibrometers, linear variable differential transformers.

Motion Magnification (MM) is an emerging video processing methodology that acts like a microscope for motion in digital videos. Hardly visible motions are magnified leaving unchanged the general topology of the image. Therefore, the micro-displacements produced by vibrations can be amplified greatly and made available to the standard frequency domain analysis. The MM was recently successfully explored as a viable method to perform modal identification, at least in laboratory. In outdoor environment ambient vibration acquisitions are unavoidably affected by significant noise disturbing the modes identification. However, the first three or four modes, which are usually the most relevant to the dynamic behaviour of most structures, can be identified with little supervision, possibly reducing the calculation requirements as much as possible. All these tasks may be accomplished using MM together with the Blind Source Separation (BSS) algorithm. BSS allows the separation of mixed signals without previously known information about the mixture. MM provides the data while the BSS improves the identification of the modes by separating their contribution within the mixed noisy signals. A case-study is proposed to explore the application of the methodology to large ancient masonry structures, which represent very challenging objects for their structural complexities and heterogeneities. In particular, the studied structure was represented by an ancient bridge, the Ponte delle Torri, Spoleto. Due to the outdoor environmental difficulties, to the state of damage of the bridge and to the high level of noise in the video footages, this case-study has to be considered a very demanding one, nevertheless the modes were identified with good approximation in comparison to the results by Operational Modal Analysis (OMA) techniques, applied to ambient vibration data from seismographs equipped with accurate triaxial velocimeters.

Large-scale seismic experimental facilities play a relevant role and provide essential contribution to the performance-based earthquake engineering. In such a context, recent advances in experimental data acquisition methodologies in large laboratories can open new perspective to the evaluation of structural performance of tested mockups under seismic load. In particular, the application of 3D motion capture systems to shaking table testing provides a unique tool for recording relative displacements of a large number of measurement points. The analysis of 3D relative displacements during dynamic tests allows to evaluate the structure deformations and to monitor the cracks formation and evolution, which can lead to the formulation of damage indices. Also, the failure mechanism could be easily visualized and analyzed by monitoring the cumulative relative displacements between markers. In addition, in-plane and out-of-plane deformations of walls could be monitored during each seismic test, providing accurate information on the torsional and bending effects. A case study is presented about a full-scale model of a masonry cross vault of the mosque of Dey, Algiers, tested at the ENEA Casaccia shaking table. The cross vault was subjected to a seismic sequence based on the 21-May-2003 earthquake recorded at Keddara station. The results obtained through the processing of the data from 67 markers located on the vault showed the potentialities of the methodology.

In the present paper an integrated approach of a wide range of non-destructive tests (NDTs) was applied to study an archeological ruined building located in Rome, the so-called Temple of Minerva Medica. Applied NDTs focused on the monument properties and environmental conditions affecting its structural behavior (geometry, thermal and mechanical properties, microclimatic monitoring, ambient vibration response). Two surveys were performed in August and December 2016 combining 3D laser scanning, thermal infrared, air temperature and relative humidity acquisitions. In addition, high resolution digital images were acquired and processed by stereo-photogrammetry Structure from Motion (SfM) methodology, carried out for detailed reconstruction of the crack pattern of the monument. In order to obtain information on the integrity and consistency of the masonry, a sonic testing of each pillar was also performed. The integration of the above NDTs provided quite complete and comprehensive understanding of the structural behavior and state of the building, reducing the amount of invasive measurements further needed.

We applied a new methodology, namely the motion magnification (MM), to the dynamic identification of historic constructions. MM acts like a microscope amplifying small motions in video sequences, therefore tiny motion patterns are made visible with the naked eye. This technique provides advantages of particular interest to the dynamic identification: no wires, no physical contact, simplicity and low costs. In this paper, we investigated the ambient vibration monitoring of historic structures in urban environments, which is a relevant issue for the health surveying and early damage detection, particularly for ancient buildings. We give an introduction to the MM methodology and describe its practical application to the frequency domain through two case-studies: the so-called Temple of Minerva Medica of Rome and the Ponte delle Torri of Spoleto. Since in the outdoor environment the MM is much more prone to noise because of the wind, shadows, atmospheric refraction, light reflection, distance from the object, weak vibration sources, the case study of the Ponte delle Torri represents a hard test-bed for MM. However, the MM estimates of the first modes showed a good agreement with the experimental data of contact velocimeters. © Published under licence by IOP Publishing Ltd.

The dynamic identification by ambient vibration data is widely used to supply information on the global health of structures through the investigation of changes in their modal parameters. It can be used even for verification of the state of damage of structures after hazardous threats, for example seismic activity. Therefore, it can play a crucial role to integrate and support conservation strategies for historic architectural assets. Sometimes, in historic constructions only a limited number of positions are accessible or usable to install sensors, and so modal analysis must be based on data from few measurement points. Moreover, they might not be the optimal positions for the studied structure, so the obtained results would need further verification. In such circumstances, the mutual validation between different modal analysis techniques can be useful to assess the reliability of results. In the present paper a case study of application to the so-called Temple of Minerva Medica, Rome, is described. Ambient vibration data were acquired in four rowing acquisition sessions carried out from July 2016 to July 2017, which is a timespan usable to assess the impact of the recent Central Italy seismic sequence. For problems related to the installation of the scaffolding only few points were available for instruments positioning. A variety of techniques were applied, including FRF, FDD, EFDD, SSI, HVSR and complex modal models. The variance of the modal parameters obtained by each different technique was utilized to provide indications on the reliability of the average values. © Published under licence by IOP Publishing Ltd.

The epidemic spreading of a disease can be described by a contact network whose nodes are persons or centers of contagion and links heterogeneous relations among them. We provide a procedure to identify multiple sources of an outbreak or their closer neighbors. Our methodology is based on a simple spectral technique requiring only the knowledge of the undirected contact graph. The algorithm is tested on a variety of graphs collected from outbreaks including fluency, H5N1, Tbc, in urban and rural areas. Results show that the spectral technique is able to identify the source nodes if the graph approximates a tree sufficiently., Comment: 5 tables, 5 figures