Search

The Fellini Museum is an exhibition hall dedicated to the Rimini film director Federico Fellini, included by the Ministry of Culture of Italy among the great national cultural projects. It was inaugurated on 19 August 2021, and it is the first worldwide exhibition hall dedicated to the famous film director. The museum, intended as a widespread museum center, is divided into three separate places in the historic center of Rimini: Sismondo Castle (built at the behest of Sigismondo Malatesta, at that time Lord of Rimini and Fano, starting from 1437 AD), Fulgor Palace and Malatesta square. The goal of the present paper is double. In the first part, as a case study, the innovative integrated system and installations planned for the optimal functioning and management of the Fellini Museum of Rimini in Italy is illustrated, showing its related complexity, due to its extension and articulation through different environments and due to the respect for architectural/historical heritage. In the second part, as dedicated and linked research, a proper Genetic Algorithms-based method, studied and applied for the optimization of the design of the wired network of the integrated system, the electrical power network and the air conditioning network is illustrated. It guarantees a decrease of realization costs, considering also the typical vincula and restrictions of already existing historical buildings, such as the considered one.

Interference signals degrade global navigation satellite system (GNSS) performance and must be mitigated. Chirp signals can be mitigated with an adaptive notch filter (ANF), but the dynamic behavior limits performance. An ANF determines the instantaneous frequency and removes interference with a notch filter. However, there are several limitations. In this article, we propose a multi-parameter adaptive notch filter (MPANF) approach that significantly enhances conventional ANFs. First, it uses an loop-bandwidth control algorithm (LBCA) to alter the loop bandwidth of an frequency-locked loop (FLL)-based adaptation algorithm to facilitate superior tracking agility-to-precision trade-off. Second, it dynamically adjusts the notch depth to switch on interference mitigation or pass the signal through. Third, it modifies the notch width to accommodate tracking stability and optimize interference signal suppression to GNSS signal removal. The presented MPANF exhibits superior performance against chirp signals, including faster response to jump discontinuities.

GNSS receivers with multi-system and multi-frequency capabilities allow more reliable positioning, especially in challenging environments. However, increased available systems and signals lead to hardware resource allocation problems. This issue escalates when ten correlators per tracked GNSS signal are used. Moreover, the communication interface between the PL and the PS affects the time complexity and challenges the capability of the maximum number of tracking channels. This paper presents the GOOSE v2, a MPSoC-based GNSS receiver, which is composed of a quad-band (L1, L2, L5/E5 and S band) RFFE and baseband digital signal processing. The SoC includes a quad-core 64-bit processor and an FPGA. The on-chip communication between the processors and the FPGA offers high bandwidth, significantly reducing the time complexity. The preliminary evaluation of this new receiver platform shows that, in addition to the legacy signals, it supports NavIC L5 and S-band signals. Furthermore, this receiver closes the tracking loops faster than its legacy version (GOOSE v1), opening the door to implementing more complex algorithms requiring higher time complexity.

This paper proposes a methodology for sentiment analysis with emphasis on the emotional aspects of people visiting the Herculaneum Archaeological Park in Italy during the period of the COVID-19 pandemic. The methodology provides a valuable means of continuous feedback on perceived risk of the site. A semantic analysis on Twitter text messages provided input to the risk management team with which they could respond immediately mitigating any apparent risk and reducing the perceived risk. A two-stage approach was adopted to prune a massively large dataset from Twitter. In the first phase, a social network analysis and visualisation tool NodeXL was used to determine the most recurrent words, which was achieved using polarity. This resulted in a suitable subset. In the second phase, the subset was subjected to sentiment and emotion mapping by survey participants. This led to a hybrid approach of using automation for pruning datasets from social media and using a human approach to sentiment and emotion analysis. Whilst suffering from COVID-19, equally, people suffered due to loneliness from isolation dictated by the World Health Organisation. The work revealed that despite such conditions, people’s sentiments demonstrated a positive effect from the online discussions on the Herculaneum site.

The performance of global navigation satellite system (GNSS) receivers is significantly affected by interference signals. For this reason, several research groups have proposed methods to mitigate the effect of different kinds of jammers. One effective method for wide-band interference mitigation (IM) is the high-rate DFT-based data manipulator (HDDM) pulse blanker (PB). It provides good performance to pulsed and frequency sparse interference. However, it and many other methods have poor performance against wide-band noise signals, which are not frequency-sparse. This article proposes to include automatic gain control (AGC) in the HDDM structure to attenuate the signal instead of removing it: the HDDM-AGC. It overcomes the wide-band noise limitation for IM at the cost of limiting mitigation capability to other signals. Previous studies with this approach were limited to only measuring the carrier-to-noise density ratio (C/N0) performance of tracking, but this article extends the analysis to include the impact of the HDDM-AGC algorithm on the position, velocity, and time (PVT) solution. It allows an end-to-end evaluation and impact assessment of mitigation to a GNSS receiver. This study compares two commercial receivers: one high-end and one low-cost, with and without HDDM IM against laboratory-generated interference signals. The results show that the HDDM-AGC provides a PVT availability and precision comparable to high-end commercial receivers with integrated mitigation for most interference types. For pulse interferences, its performance is superior. Further, it is shown that degradation is minimized against wide-band noise interferences. Regarding low-cost receivers, the PVT availability can be increased up to 40% by applying an external HDDM-AGC.

Interference can significantly degrade the performance of global navigation satellite system (GNSS) receivers. Therefore, mitigation methods are required to ensure reliable operations. However, as there are different types of interference, robust, multi-purpose mitigation algorithms are needed. This paper describes the most popular state-of-the-art interference mitigation techniques. The high-rate DFT-based data manipulator (HDDM) is proposed as a possible solution to overcome their limitations. This paper presents a hardware implementation of the HDDM algorithm. The hardware HDDM module is integrated in three different receivers equipped with analog radio-frequency (RF) front-ends supporting signals with different dynamic range. The resource utilization and power consumption is evaluated for the three cases. The algorithm is compared to a low-end mass-market receiver and a high-end professional receiver with basic and sophisticated interference mitigation capabilities, respectively. Different type of interference are used to compare the mitigation capabilities of the receivers under test. Results of the HDDM hardware implementation achieve the similar or improved performance to the state of the art. With more complex interferences, like frequency hopping or pulsed, the HDDM shows even better performance.

Abstract The aim of this study is the risk analysis evaluation about argon release from the GERDA experiment in the Gran Sasso underground National Laboratories (LNGS) of the Italian National Institute for Nuclear Physics (INFN). The GERDA apparatus, located in Hall A of the LNGS, is a facility with germanium detectors located in a wide tank filled with about 70 m3 of cold liquefied argon. This cryo-tank sits in another water-filled tank (700 m3) at atmospheric pressure. In such cryogenic processes, the main cause of an accidental scenario is lacking insulation of the cryo-tank. A preliminary HazOp analysis has been carried out on the whole system. The risk assessment identified two possible top-events: explosion due to a Rapid Phase Transition - RPT and argon runaway evaporation. Risk analysis highlighted a higher probability of occurrence of the latter top event. To avoid emission in Hall A, the HazOp, Fault Tree and Event tree analyses of the cryogenic gas extraction and ventilation plant have been made. The failures related to the ventilation system are the main cause responsible for the occurrence. To improve the system reliability some corrective actions were proposed: the use of UPS and the upgrade of damper opening devices. Furthermore, the Human Reliability Analysis identified some operating and management improvements: action procedure optimization, alert warnings and staff training. The proposed model integrates the existing analysis techniques by applying the results to an atypical work environment and there are useful suggestions for improving the system reliability.