Structure-from-Motion 3D Reconstruction of the Historical Overpass Ponte della Cerra: A Comparison between MicMac® Open Source Software and Metashape®

In recent years, the performance of free-and-open-source software (FOSS) for image processing has significantly increased. This trend, as well as technological advancements in the unmanned aerial vehicle (UAV) industry, have opened blue skies for both researchers and surveyors. In this study, we aimed to assess the quality of the sparse point cloud obtained with a consumer UAV and a FOSS. To achieve this goal, we also process the same image dataset with a commercial software package using its results as a term of comparison. Various analyses were conducted, such as the image residuals analysis, the statistical analysis of GCPs and CPs errors, the relative accuracy assessment, and the Cloud-to-Cloud distance comparison. A support survey was conducted to measure 16 markers identified on the object. In particular, 12 of these were used as ground control points to scale the 3D model, while the remaining 4 were used as check points to assess the quality of the scaling procedure by examining the residuals. Results indicate that the sparse clouds obtained are comparable. MicMac® has mean image residuals equal to 0.770 pixels while for Metashape® is 0.735 pixels. In addition, the 3D errors on control points are similar: the mean 3D error for MicMac® is equal to 0.037 m with a standard deviation of 0.017 m, whereas for Metashape®, it is 0.031 m with a standard deviation equal to 0.015 m. The present work represents a preliminary study: a comparison between software packages is something hard to achieve, given the secrecy of the commercial software and the theoretical differences between the approaches. This case study analyzes an object with extremely complex geometry; it is placed in an urban canyon where the GNSS support can not be exploited. In addition, the scenario changes continuously due to the vehicular traffic

Artificial neural networks for resources optimization in energetic environment

Resource Planning Optimization (RPO) is a common task that many companies need to face to get several benefits, like budget improvements and run-time analyses. However, even if it is often solved by using several software products and tools, the great success and validity of the Artificial Intelligence-based approaches, in many research fields, represent a huge opportunity to explore alternative solutions for solving optimization problems. To this purpose, the following paper aims to investigate the use of multiple Artificial Neural Networks (ANNs) for solving a RPO problem related to the scheduling of different Combined Heat & Power (CHP) generators. The experimental results, carried out by using data extracted by considering a real Microgrid system, have confirmed the effectiveness of the proposed approach

Low-cost GNSS software receiver performance assessment

The Software-Defined Receiver (SDR) is a rapidly evolving technology which is a useful tool for researchers and allows users an extreme level customization. The main aim of this work is the assessment of the performance of the combination consisting of the Global Navigation Satellite Systems software receiver (GNSS-SDR), developed by CTTC (Centre Tecnològic de Telecomunicacions de la Catalunya), and a low-cost front-end. GNSS signals were acquired by a Nuand bladeRF x-40 front-end fed by the TOPCON PG-A1 antenna. Particular attention was paid to the study of the clock-steering mechanism due to the low-cost characteristics of the bladeRF x-40 clock. Two different tests were carried out: In the first test, the clock-steering algorithm was activated, while in the second, it was deactivated. The tests were conducted in a highly degraded scenario where the receiver was surrounded by tall buildings. Single-Point and Code Differential positioning were computed. The achieved results show that the steering function guarantees the availability of more solutions, but the DRMS is quite the same in the two tests

A federated approach to Android malware classification through Perm-Maps

In the last decades, mobile-based apps have been increasingly used in several application fields for many purposes involving a high number of human activities. Unfortunately, in addition to this, the number of cyber-attacks related to mobile platforms is increasing day-by-day. However, although advances in Artificial Intelligence science have allowed addressing many aspects of the problem, malware classification tasks are still challenging. For this reason, the following paper aims to propose new special features, called permission maps (Perm-Maps), which combine information related to the Android permissions and their corresponding severity levels. Such features have proven to be very effective in classifying different malware families through the usage of a convolutional neural network. Also, the advantages introduced by the Perm-Maps have been enhanced by a training process based on a federated logic. Experimental results show that the proposed approach achieves up to a 3% improvement in average accuracy with respect to J48 trees and Naive Bayes classifier, and up to 16% compared to multi-layer perceptron classifier. Furthermore, the combined use of Perm-Maps and federated logic allows dealing with unbalanced training datasets with low computational efforts

Assessment of dual frequency GNSS observations from a Xiaomi Mi 8 android smartphone and positioning performance analysis

On May 2018 the world’s first dual-frequency Global Navigation Satellite System (GNSS) smartphone produced by Xiaomi equipped with a Broadcom BCM47755 chip was launched. It is able to receive L1/E1/ and L5/E5 signals from GPS, Galileo, Beidou, and GLONASS (GLObal NAvigation Satellite System) satellites. The main aim of this work is to achieve the phone’s position by using multi-constellation, dual frequency pseudorange and carrier phase raw data collected from the smartphone. Furthermore, the availability of dual frequency raw data allows to assess the multipath performance of the device. The smartphone’s performance is compared with that of a geodetic receiver. The experiments were conducted in two different scenarios to test the smartphone under different multipath conditions. Smartphone measurements showed a lower C/N0 and higher multipath compared with those of the geodetic receiver. This produced negative effects on single-point positioning as showed by high root mean square error (RMS). The best positioning accuracy for single point was obtained with the E5 measurements with a DRMS (horizontal root mean square error) of 4.57 m. For E1/L1 frequency, the 2DRMS was 5.36 m. However, the Xiaomi Mi 8, thanks to the absence of the duty cycle, provided carrier phase measurements used for a static single frequency relative positioning with an achieved 2DRMS of 1.02 and 1.95 m in low and high multipath sites, respectively

Variable dampers to mitigate structural demand to wind turbines: The role of the monitoring system features for the effectiveness of the control strategy

In the last decade, some researchers and professionals have been engaged in the study of methods and techniques that can build high wind turbines while containing construction costs within the limits of economic convenience. Among the most promising solutions is that of using innovative devices to mitigate the structural demand for the towers. The reduction in the stress demand in the foundation makes the strategy particularly interesting for the repowering of existing plants, where it is convenient not to demolish and rebuild the foundation, but rather to reuse the existing one for the new plant. A semi-active vibration control strategy, based on the adoption of controllable dissipative devices, is presented herein. The proposed technique requires the tower to be equipped with a measurement system suitable for the real time monitoring of structural response. Performing reliable high-frequency measurements of the horizontal displacement of points located at heights of tens of meters is not simple. With the purpose of assessing the efficiency and feasibility of Global Navigation Satellite System (GNSS)-based systems for the control of wind turbine structures, the proposed paper tries to investigate the characteristics and data processing techniques that are able to make the GNSS useful for such applications. Several numerical simulations were carried out with reference to a case-study wind turbine to quantitatively assess how the performance of the control system changes as the features of the monitoring system worsen, and finally to draw conclusions and suggestions for the minimum performance that monitoring devices must have for an effective reduction in structural demand

Thermal Adaptation of Conformational Dynamics in Ribonuclease H

The relationship between inherent internal conformational processes and enzymatic activity or thermodynamic stability of proteins has proven difficult to characterize. The study of homologous proteins with differing thermostabilities offers an especially useful approach for understanding the functional aspects of conformational dynamics. In particular, ribonuclease HI (RNase H), an 18 kD globular protein that hydrolyzes the RNA strand of RNA:DNA hybrid substrates, has been extensively studied by NMR spectroscopy to characterize the differences in dynamics between homologs from the mesophilic organism E. coli and the thermophilic organism T. thermophilus. Herein, molecular dynamics simulations are reported for five homologous RNase H proteins of varying thermostabilities and enzymatic activities from organisms of markedly different preferred growth temperatures. For the E. coli and T. thermophilus proteins, strong agreement is obtained between simulated and experimental values for NMR order parameters and for dynamically averaged chemical shifts, suggesting that these simulations can be a productive platform for predicting the effects of individual amino acid residues on dynamic behavior. Analyses of the simulations reveal that a single residue differentiates between two different and otherwise conserved dynamic processes in a region of the protein known to form part of the substrate-binding interface. Additional key residues within these two categories are identified through the temperature-dependence of these conformational processes

Precise point positioning with single and dual-frequency multi-GNSS android smartphones

The new generation of Android smartphones is equipped with high performance Global Navigation Satellite System (GNSS) chips capable of tracking dual frequency multi-constellation data. Moreover, starting from version 9 of Android users can disable the duty cycle power saving option thus good quality pseudorange and carrier phase raw data are available thus the application of Precise Point Positioning (PPP) algorithm becomes more and more interesting. The main aim of this work is to assess the PPP performance of the first dual-frequency GNSS smartphone produced by Xiaomi equipped with a Broadcom BCM47755. The advantage of acquire dual frequency data is highlighted by comparing the performance obtained by Xiaomi with that of a single frequency smartphone the Samsung S8. The horizontal and vertical accuracy achieved by Xiaomi are of 0.51 m and 6 m respectively while those achieved by Samsung are 5.64 m for 15 m for horizontal and vertical

European Linguistic Monitor (ELM)

The European Linguistic Monitor (ELM) is a project conceived as an online system to collect data and to provide detailed up-to-date information on the linguistic situation and development in the various member state of the European Union. This paper discusses the criteria adopted and the third version of ELM