This page has only limited features, please log in for full access.
The seismic assessment of historical monuments typically involves many issues, the most crucial of which are: retrieving geometrical and mechanical data; implementing a suitable numerical model; choosing the more appropriate type of analysis and properly interpreting the results. The more well-managed these issues are the better the reliability of the seismic assessment. The Civic Tower of L'Aquila (Italy) is considered in this paper as a typical case in which lack of data and discrepancy of sources make the seismic assessment hard to be suitably performed. The key role of the identification of the numerical model was firstly evidenced. Different numerical models were implemented to identify the best-fitting geometrical and mechanical properties of the structure. The considered case-study also led to the discussion of some issues concerning the identification of the numerical model of historical towers. Code-compliant linear and non-linear dynamic analyses were then carried out to compare the seismic performance of the tower assessed through the different methods based on regulations. A concrete damage plasticity model for masonry and a set of spectrum-consistent earthquakes were adopted. The stress maps, the horizontal displacement peaks (useful to avoid the pounding phenomenon with the adjacent Margherita palace), and the evolution of damage were investigated. The study highlighted that the widely adopted response-spectrum modal analysis (RSMA) may underestimate -even remarkably-the displacement demand compared to the more rigorous time-history linear analysis (THLA), this being an inconsistency of the code-compliant linear analyses. On the other hand, the results of the non-linear time-history analysis (NLTHA) confirmed the displacement demand predicted by the THLA, while the damage evolution under tensile stress was found in agreement with the crack pattern detected on the structure. The influence of the vertical component of the earthquake was also investigated, founding that the vertical component of the ground motion does not significantly affect the results.
Maria Cristina Porcu; Elisa Montis; Manuel Saba. Role of model identification and analysis method in the seismic assessment of historical masonry towers. Journal of Building Engineering 2021, 43, 103114 .
AMA StyleMaria Cristina Porcu, Elisa Montis, Manuel Saba. Role of model identification and analysis method in the seismic assessment of historical masonry towers. Journal of Building Engineering. 2021; 43 ():103114.
Chicago/Turabian StyleMaria Cristina Porcu; Elisa Montis; Manuel Saba. 2021. "Role of model identification and analysis method in the seismic assessment of historical masonry towers." Journal of Building Engineering 43, no. : 103114.
An effective seismic design entails many issues related to the capacity-based assessment of the non-linear structural response under strong earthquakes. While very powerful structural calculation programs are available to assist the designer in the code-based seismic analysis, an optimal choice of the design parameters leading to the best performance at the lowest cost is not always assured. The present paper proposes a procedure to cost-effectively design earthquake-resistant buildings, which is based on the inversion of an artificial neural network and on an optimization algorithm for the minimum total cost under building code constraints. An exemplificative application of the method to a reinforced-concrete multi-story building, with seismic demands corresponding to a medium-seismicity Italian zone, is shown. Three design-governing parameters are assumed to build the input matrix, while eight capacity-design target requirements are assigned for the output dataset. A non-linear three-dimensional concentrated plasticity model of the structure is implemented, and time-history dynamic analyses are carried out with spectrum-consistent ground motions. The results show the promising ability of the proposed approach for the optimal design of earthquake-resistant structures.
Carlo Calledda; Augusto Montisci; Maria Porcu. Optimal Design of Earthquake-Resistant Buildings Based on Neural Network Inversion. Applied Sciences 2021, 11, 4654 .
AMA StyleCarlo Calledda, Augusto Montisci, Maria Porcu. Optimal Design of Earthquake-Resistant Buildings Based on Neural Network Inversion. Applied Sciences. 2021; 11 (10):4654.
Chicago/Turabian StyleCarlo Calledda; Augusto Montisci; Maria Porcu. 2021. "Optimal Design of Earthquake-Resistant Buildings Based on Neural Network Inversion." Applied Sciences 11, no. 10: 4654.
The literature in the field of archaeological predictive models has grown in the last years, looking for new factors the most effective methods to introduce. However, where predictive models are used for archaeological heritage management, they could benefit from using a more speedy and consequently useful methods including some well-consolidated factors studied in the literature. In this paper, an operative archaeological predictive model is developed, validated and discussed, in order to test its effectiveness. It is applied to Yangshao period (5000–3000 BC) in the Songshan area, where Chinese civilization emerged and developed, and uses 563 known settlement sites. The satisfactory results herein achieved clearly suggest that the model herein proposed can be reliably used to predict the geographical location of unknown settlements.
Lijie Yan; Peng Lu; Panpan Chen; Maria Danese; Xiang Li; Nicola Masini; Xia Wang; Lanbo Guo; Dong Zhao. Towards an Operative Predictive Model for the Songshan Area during the Yangshao Period. ISPRS International Journal of Geo-Information 2021, 10, 217 .
AMA StyleLijie Yan, Peng Lu, Panpan Chen, Maria Danese, Xiang Li, Nicola Masini, Xia Wang, Lanbo Guo, Dong Zhao. Towards an Operative Predictive Model for the Songshan Area during the Yangshao Period. ISPRS International Journal of Geo-Information. 2021; 10 (4):217.
Chicago/Turabian StyleLijie Yan; Peng Lu; Panpan Chen; Maria Danese; Xiang Li; Nicola Masini; Xia Wang; Lanbo Guo; Dong Zhao. 2021. "Towards an Operative Predictive Model for the Songshan Area during the Yangshao Period." ISPRS International Journal of Geo-Information 10, no. 4: 217.
Osvaldo Gervasi; Beniamino Murgante; Sanjay Misra; Chiara Garau; Ivan Blečić; David Taniar; Bernady O. Apduhan; Ana Maria A. C. Rocha; Eufemia Tarantino; Carmelo Maria Torre; Yeliz Karaca. Correction to: Computational Science and Its Applications – ICCSA 2020. Computers and Games 2021, 12249, C1 -C1.
AMA StyleOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Chiara Garau, Ivan Blečić, David Taniar, Bernady O. Apduhan, Ana Maria A. C. Rocha, Eufemia Tarantino, Carmelo Maria Torre, Yeliz Karaca. Correction to: Computational Science and Its Applications – ICCSA 2020. Computers and Games. 2021; 12249 ():C1-C1.
Chicago/Turabian StyleOsvaldo Gervasi; Beniamino Murgante; Sanjay Misra; Chiara Garau; Ivan Blečić; David Taniar; Bernady O. Apduhan; Ana Maria A. C. Rocha; Eufemia Tarantino; Carmelo Maria Torre; Yeliz Karaca. 2021. "Correction to: Computational Science and Its Applications – ICCSA 2020." Computers and Games 12249, no. : C1-C1.
According to the current European and Italian scenario related to urban regeneration, cultural and landscape heritage valorization is being enhanced by the activation of innovative processes and new emerging approaches. These involve the development of methodologies and tools that can address decision-making processes based on creative practices consistent with a concept named “low-entropy economy” in this paper. The low-entropy economy represents an economic approach based on the minimization of physical urban transformation and the enhancement of the existing heritage. In this perspective, the research aims to develop the Cultural Heritage Low Entropy Enhancement (CHLEE) approach by exploring how some frugal experiences have promoted cultural heritage enhancement and related complex values through a program of temporary uses and activities able to produce new values, where the human experience is essential. A crucial role is represented by the heterogeneity of creative practices that contribute to identifying and implementing innovative management and governance models. The analysis of creative practices, based upon the ex post evaluation of some Italian case studies across the PROMETHEE-GAIA multicriteria method, is able to show how these experiences build innovation ecosystems and improve the ex ante evaluation for new strategies and policies, underlining strengths, weaknesses, and milestones that shape creative experiences as drivers of urban competitiveness.
Maria Cerreta; Gaia Daldanise; Eleonora Giovene di Girasole; Carmelo Torre. A Cultural Heritage Low Entropy Enhancement Approach: An Ex Post Evaluation of Creative Practices. Sustainability 2021, 13, 2765 .
AMA StyleMaria Cerreta, Gaia Daldanise, Eleonora Giovene di Girasole, Carmelo Torre. A Cultural Heritage Low Entropy Enhancement Approach: An Ex Post Evaluation of Creative Practices. Sustainability. 2021; 13 (5):2765.
Chicago/Turabian StyleMaria Cerreta; Gaia Daldanise; Eleonora Giovene di Girasole; Carmelo Torre. 2021. "A Cultural Heritage Low Entropy Enhancement Approach: An Ex Post Evaluation of Creative Practices." Sustainability 13, no. 5: 2765.
To detect the presence of damage, many structural health monitoring techniques exploit the nonlinear features that typically affect the otherwise linear dynamic response of structural components with internal defects. One of them is the Scaling Subtraction Method (SSM), which evaluates nonlinear features of the response to a high-amplitude harmonic excitation by subtracting a scaled reference signal. Originally tested on granular materials, the SSM was shown to be effective for composite materials as well. However, the dependence of the technique efficiency on the testing frequency, usually selected among the natural frequencies of the system, may limit its application in practice. This paper investigates the feasibility of applying the SSM through a broadband impulsive excitation, which would avoid the need of a preliminary modal analysis and address the issue of the proper selection of the excitation frequency. A laminated composite beam was tested in intact and damaged conditions under both scaled harmonic excitations of different frequency and broadband impulsive signals of scaled amplitude. Two damage indicators working on the frequency domain were introduced. The results showed a good sensitivity of the SSM to the presence and level of impact damage in composite beams when applied through a broadband impulsive excitation.
Gabriela Loi; Maria Cristina Porcu; Francesco Aymerich. Impact Damage Detection in Composite Beams by Analysis of Non-Linearity under Pulse Excitation. Journal of Composites Science 2021, 5, 39 .
AMA StyleGabriela Loi, Maria Cristina Porcu, Francesco Aymerich. Impact Damage Detection in Composite Beams by Analysis of Non-Linearity under Pulse Excitation. Journal of Composites Science. 2021; 5 (2):39.
Chicago/Turabian StyleGabriela Loi; Maria Cristina Porcu; Francesco Aymerich. 2021. "Impact Damage Detection in Composite Beams by Analysis of Non-Linearity under Pulse Excitation." Journal of Composites Science 5, no. 2: 39.
According to the current European and Italian scenario related to urban re-generation, cultural and landscape heritage, valorisation is being also enhanced by the activation of innovative processes. These involve the development of methodologies and tools that are able to address decision-making processes among low entropy economy, complex values and creative practices. In this perspective, the research aims to investigate the possibilities of developing a Cultural Heritage Low Entropy Enhancement (CHLEE) approach by considering how the complex values of cultural heritage can vary not only through a physical transformation of spaces but also through a program of uses and activities able to produce new values, where the human experience is essential. This type of model modifies the objectives that characterise the valorisation of cultural heritage and landscape, recognising that the fruition is no longer “consumerist” but “experiential”. A crucial role is represented by the heterogeneity of creative practices that contribute to the identificationidentifying and implementation ofimplementing innovative management and governance models. The present paper explores the components of creative regenerative processes, based upon the ex-post evaluation of some Italian experiments, across the PROMETHEE-GAIA multi-criteria method, to understand how creative experiences are building innovation ecosystem thanks to low entropy economy and improve the ex-ante evaluation for new strategies and policies.
Maria Cerreta; Gaia Daldanise; Eleonora Giovene di Girasole; Carmelo Maria Torre. Towards the Cultural Heritage Low Entropy Enhancement Approach: An Ex-post Evaluation of Creative Regeneration Practices. 2021, 1 .
AMA StyleMaria Cerreta, Gaia Daldanise, Eleonora Giovene di Girasole, Carmelo Maria Torre. Towards the Cultural Heritage Low Entropy Enhancement Approach: An Ex-post Evaluation of Creative Regeneration Practices. . 2021; ():1.
Chicago/Turabian StyleMaria Cerreta; Gaia Daldanise; Eleonora Giovene di Girasole; Carmelo Maria Torre. 2021. "Towards the Cultural Heritage Low Entropy Enhancement Approach: An Ex-post Evaluation of Creative Regeneration Practices." , no. : 1.
The Incremental Dynamic Analysis (IDA) assesses the global collapse capacity of a structure by plotting its maximum inelastic response, obtained through a non-linear time-history analysis, versus the scaled intensity of different input earthquakes. The seismic intensity is often measured through the spectral acceleration at the fundamental elastic period. However, this can produce highly variable results. An alternative method is presented in this paper that relies on the elongated period, calculated either from the Fourier spectrum of the acceleration at a target building point (inelastic peak period) or from a smooth Fourier spectrum (inelastic smooth peak period). By referring to a reference reinforced concrete building and to a set of 10 spectrum-consistent earthquakes, the paper presents the results of a wide investigation. First, the variation in the elongated period as a function of the seismic intensity is discussed. Then, the effectiveness of the proposed method is assessed by comparing the IDA curves to those obtained through the elastic period or through approximate values of the elongated period given in the literature. The results show that the alternative IDA procedure generates curves with less-dispersed collapse thresholds. A statistical analysis shows significant improvements in the results when the inelastic smooth peak period is adopted.
Juan Carlos Vielma; Maria Cristina Porcu; Nelson López. Intensity Measure Based on a Smooth Inelastic Peak Period for a More Effective Incremental Dynamic Analysis. Applied Sciences 2020, 10, 8632 .
AMA StyleJuan Carlos Vielma, Maria Cristina Porcu, Nelson López. Intensity Measure Based on a Smooth Inelastic Peak Period for a More Effective Incremental Dynamic Analysis. Applied Sciences. 2020; 10 (23):8632.
Chicago/Turabian StyleJuan Carlos Vielma; Maria Cristina Porcu; Nelson López. 2020. "Intensity Measure Based on a Smooth Inelastic Peak Period for a More Effective Incremental Dynamic Analysis." Applied Sciences 10, no. 23: 8632.
Maria Cristina Porcu. Determination of the Singularity Order at the Interface between Two Dissimilar Materials in a Simple Lap Joint. 2020, 1 .
AMA StyleMaria Cristina Porcu. Determination of the Singularity Order at the Interface between Two Dissimilar Materials in a Simple Lap Joint. . 2020; ():1.
Chicago/Turabian StyleMaria Cristina Porcu. 2020. "Determination of the Singularity Order at the Interface between Two Dissimilar Materials in a Simple Lap Joint." , no. : 1.
This paper investigates how agri-food research and innovation (R&I) activity may interact with sustainable local development processes. The focus is on smart specialisation strategies and partnerships between agri-food business and research organisations, established under the open innovation paradigm. An exploratory study is carried out on recent (2010–19) agri-food R&I activity in Puglia (Italy), covering both projects and patents carried out by 47 research centres (affiliated to any of 11 research institutions) and 40 agri-food enterprises. Beside project data analysis based on categorisation, the methodology applied social network analysis to partnerships. Findings point to Sustainable Manufacturing and Human and Environmental Health being the prevalent target areas of innovation activity, thus resulting in some form of sustainable agricultural intensification, with a bias towards Industrial Biotechnology, Advanced Materials and Nanotechnology. Open innovation approaches seem to be still phasing in, and the innovation potential of agri-food enterprises appears to be largely untapped. Future research may address the friction between industry-driven smart specialisation strategies and place-based innovation patterns that harness the intangible potential of social and relational capital.
Manuela Persia; Pasquale Balena; Alessandro Bonifazi; Maria Immacolata Marzulli; Antonio Orlando; Carmelo M. Torre. Sustainable Local Development and Smart Specialisation Strategies: Recent Developments in Agri-food Research and Innovation Partnerships in Puglia, Italy. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12253, 221 -236.
AMA StyleManuela Persia, Pasquale Balena, Alessandro Bonifazi, Maria Immacolata Marzulli, Antonio Orlando, Carmelo M. Torre. Sustainable Local Development and Smart Specialisation Strategies: Recent Developments in Agri-food Research and Innovation Partnerships in Puglia, Italy. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12253 ():221-236.
Chicago/Turabian StyleManuela Persia; Pasquale Balena; Alessandro Bonifazi; Maria Immacolata Marzulli; Antonio Orlando; Carmelo M. Torre. 2020. "Sustainable Local Development and Smart Specialisation Strategies: Recent Developments in Agri-food Research and Innovation Partnerships in Puglia, Italy." Transactions on Petri Nets and Other Models of Concurrency XV 12253, no. : 221-236.
The Mediterranean ecosystem represents an important natural resource, being able to produce ecosystem services, has both economic and social repercussions, especially if located in urban and peri-urban areas. In the last decades, increased forest vulnerability is being reflected in a larger number of severe decline episodes associated mainly with drought conditions. In this context, the Mediterranean area shows high forest vulnerability and a subsequent decline in its natural renewal rate. In this context, the objective of this research is to evaluate the different vegetation indices to monitor the effect of drought on the health of the Castelporziano pine wood. For this purpose, we used the NDVI, NDII and NMDI, provided by ESA Sentinel-2 images and field observations, to monitor the health status of a historic pinewood that has recently been affected by a rapid spread of parasites (Tomicus destruens Woll.). The application of these indices, on the scale of the entire pinewood, showed that the NDVI and NDII indices differentiate better the changes in vegetative health status for the observed period than the NMDI. Moreover, NDVI and NDII were applied, based on the classifications made, to volume and age classes. Ultimately, these preliminary results require further studies to better understand the potential and limiting factors of the indices used in monitoring pinewoods under stress due to aridity.
Benedetta Cucca; Fabio Recanatesi; Maria Nicolina Ripa. Evaluating the Potential of Vegetation Indices in Detecting Drought Impact Using Remote Sensing Data in a Mediterranean Pinewood. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12253, 50 -62.
AMA StyleBenedetta Cucca, Fabio Recanatesi, Maria Nicolina Ripa. Evaluating the Potential of Vegetation Indices in Detecting Drought Impact Using Remote Sensing Data in a Mediterranean Pinewood. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12253 ():50-62.
Chicago/Turabian StyleBenedetta Cucca; Fabio Recanatesi; Maria Nicolina Ripa. 2020. "Evaluating the Potential of Vegetation Indices in Detecting Drought Impact Using Remote Sensing Data in a Mediterranean Pinewood." Transactions on Petri Nets and Other Models of Concurrency XV 12253, no. : 50-62.
In this work, we tested the reliability of two different methods of automated landform classification (ACL) in three geological domains of the southern Italian chain with contrasting morphological features. ACL maps deriving from the TPI-based (topographic position index) algorithm are strictly dependent to the search input parameters and they are not able to fully capture landforms of different size. Geomorphons-based classification has shown a higher potential and can represent a powerful method of ACL, although it should be improved with the introduction of additional DEM-based parameters for the extraction of landform classes.
Dario Gioia; Maria Danese; Mario Bentivenga; Eva Pescatore; Vincenzo Siervo; Salvatore Ivo Giano. Comparison of Different Methods of Automated Landform Classification at the Drainage Basin Scale: Examples from the Southern Italy. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12250, 696 -708.
AMA StyleDario Gioia, Maria Danese, Mario Bentivenga, Eva Pescatore, Vincenzo Siervo, Salvatore Ivo Giano. Comparison of Different Methods of Automated Landform Classification at the Drainage Basin Scale: Examples from the Southern Italy. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12250 ():696-708.
Chicago/Turabian StyleDario Gioia; Maria Danese; Mario Bentivenga; Eva Pescatore; Vincenzo Siervo; Salvatore Ivo Giano. 2020. "Comparison of Different Methods of Automated Landform Classification at the Drainage Basin Scale: Examples from the Southern Italy." Transactions on Petri Nets and Other Models of Concurrency XV 12250, no. : 696-708.
Multiple sclerosis (MS) is an autoimmune demyelinating disease that affects one’s central nervous system. The disease has a number lesion states. One of them is known as active, or enhancing, and indicates that a lesion is under an inflammatory condition. This specific case is of interest to radiologists since it is commonly associated with the period of time a patient suffers most from the effects of MS. To identify which lesions are active, a Gadolinium-based contrast is injected in the patient prior to a magnetic resonance imaging procedure. The properties of the contrast medium allow it to enhance active lesions, making them distinguishable from nonactive ones in T1-w images. However, studies from various research groups in recent years indicate that Gadolinium-based contrasts tend to accumulate in the body after a number of injections. Since a comprehensive understanding of this accumulation is not yet available, medical agencies around the world have been restricting its usage to cases only where it is absolutely necessary. In this work we propose a supervised algorithm to distinguish active from nonactive lesions in FLAIR images, thus eliminating the need for contrast injections altogether. The classification task was performed using textural and enhanced features as input to the XGBoost classifier on a voxel level. Our database comprised 54 MS patients (33 with active lesions and 21 with nonactive ones) with a total of 22 textural and enhanced features obtained from Run Length and Gray Level Co-occurrence Matrices. The average precision, recall and F1-score results in a 6-fold cross-validation for active and nonactive classes were 0.892, 0.968, 0.924 and 0.994, 0.987, 0.991, respectively. Moreover, from a lesion perspective, the algorithm misclassified only 3 active lesions out of 157. These results indicate our tool can be used by physicians to get information about active MS lesions in FLAIR images without using any kind of contrast, thus improving one’s health and also reducing the cost of MRI procedures for MS patients.
Paulo G. L. Freire; Marcos Hideki Idagawa; Enedina Maria Lobato De Oliveira; Nitamar Abdala; Henrique Carrete; Ricardo J. Ferrari. Classification of Active Multiple Sclerosis Lesions in MRI Without the Aid of Gadolinium-Based Contrast Using Textural and Enhanced Features from FLAIR Images. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12250, 60 -74.
AMA StylePaulo G. L. Freire, Marcos Hideki Idagawa, Enedina Maria Lobato De Oliveira, Nitamar Abdala, Henrique Carrete, Ricardo J. Ferrari. Classification of Active Multiple Sclerosis Lesions in MRI Without the Aid of Gadolinium-Based Contrast Using Textural and Enhanced Features from FLAIR Images. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12250 ():60-74.
Chicago/Turabian StylePaulo G. L. Freire; Marcos Hideki Idagawa; Enedina Maria Lobato De Oliveira; Nitamar Abdala; Henrique Carrete; Ricardo J. Ferrari. 2020. "Classification of Active Multiple Sclerosis Lesions in MRI Without the Aid of Gadolinium-Based Contrast Using Textural and Enhanced Features from FLAIR Images." Transactions on Petri Nets and Other Models of Concurrency XV 12250, no. : 60-74.
This article describes the primary characteristics of a tool developed to perform a control loop performance assessment, named SELC due to its name in Spanish. With this tool, we expect to increase the reliability and efficiency of productive processes in Colombia’s industry. A brief description of SELC’s functionality and a literature review about the different techniques integrated is presented. Finally, the results and conclusions of the testing phase were presented, performed with both simulated and real data. The actual data comes from an online industrial repository provided by the South African Council for Automation and Control (SACAC).
Javier Jiménez-Cabas; Fabián Manrique-Morelos; Farid Meléndez-Pertuz; Andrés Torres-Carvajal; Jorge Cárdenas-Cabrera; Carlos Collazos-Morales; Ramón E. R. González. Development of a Tool for Control Loop Performance Assessment. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12250, 239 -254.
AMA StyleJavier Jiménez-Cabas, Fabián Manrique-Morelos, Farid Meléndez-Pertuz, Andrés Torres-Carvajal, Jorge Cárdenas-Cabrera, Carlos Collazos-Morales, Ramón E. R. González. Development of a Tool for Control Loop Performance Assessment. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12250 ():239-254.
Chicago/Turabian StyleJavier Jiménez-Cabas; Fabián Manrique-Morelos; Farid Meléndez-Pertuz; Andrés Torres-Carvajal; Jorge Cárdenas-Cabrera; Carlos Collazos-Morales; Ramón E. R. González. 2020. "Development of a Tool for Control Loop Performance Assessment." Transactions on Petri Nets and Other Models of Concurrency XV 12250, no. : 239-254.
Recent advances in spatial methods of digital elevation model (DEMs) analysis have addressed many research topics on the assessment of morphometric parameters of the landscape. Development of computer algorithms for calculating the geomorphometric properties of the Earth’s surface has allowed for expanding of some methods in the semi-automatic recognition and classification of landscape features. In such a way, several papers have been produced, documenting the applicability of the landform classification based on map algebra. The Topographic Position Index (TPI) is one of the most widely used parameters for semi-automated landform classification using GIS software. The aim was to apply the TPI classes for landform classification in the Basilicata Region (Southern Italy). The Basilicata Region is characterized by an extremely heterogeneous landscape and geological features. The automated landform extraction, starting from two different resolution DEMs at 20 and 5 m-grids, has been carried out by using three different GIS software: Arcview, Arcmap, and SAGA. Comparison of the landform maps resulting from each software at a different scale has been realized, furnishing at the end the best landform map and consequently a discussion over which is the best software implementation of the TPI method.
Salvatore Ivo Giano; Maria Danese; Dario Gioia; Eva Pescatore; Vincenzo Siervo; Mario Bentivenga. Tools for Semi-automated Landform Classification: A Comparison in the Basilicata Region (Southern Italy). Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12250, 709 -722.
AMA StyleSalvatore Ivo Giano, Maria Danese, Dario Gioia, Eva Pescatore, Vincenzo Siervo, Mario Bentivenga. Tools for Semi-automated Landform Classification: A Comparison in the Basilicata Region (Southern Italy). Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12250 ():709-722.
Chicago/Turabian StyleSalvatore Ivo Giano; Maria Danese; Dario Gioia; Eva Pescatore; Vincenzo Siervo; Mario Bentivenga. 2020. "Tools for Semi-automated Landform Classification: A Comparison in the Basilicata Region (Southern Italy)." Transactions on Petri Nets and Other Models of Concurrency XV 12250, no. : 709-722.
Among the many causes of collapse of civil structures, those related to the downfall of foundations are crucial for their likely catastrophic consequences. Interferometric synthetic aperture radar (InSAR) techniques may help monitoring the time evolution of ground displacements affecting engineered structures in large urban areas. Artificial neural networks can be exploited to analyze the huge amount of data that is collected over long periods of time on very dense grid of geographical points. The paper presents a neural network-based analysis tool, able to evidence similarities among time series acquired in different points and times. This tool could support an early-warning system, aiming to forecast critical events in urban areas. The implemented procedure is tested on a dataset of InSAR time series recorded over an area of the city of London.
Augusto Montisci; Maria Cristina Porcu. Self-organizing-Map Analysis of InSAR Time Series for the Early Warning of Structural Safety in Urban Areas. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12255, 864 -876.
AMA StyleAugusto Montisci, Maria Cristina Porcu. Self-organizing-Map Analysis of InSAR Time Series for the Early Warning of Structural Safety in Urban Areas. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12255 ():864-876.
Chicago/Turabian StyleAugusto Montisci; Maria Cristina Porcu. 2020. "Self-organizing-Map Analysis of InSAR Time Series for the Early Warning of Structural Safety in Urban Areas." Transactions on Petri Nets and Other Models of Concurrency XV 12255, no. : 864-876.
This work focuses on groundwater resources contaminations identification. The problem of identifying an unknown pollution source in polluted aquifers, based on known contaminant concentrations measurement in the studied areas, is part of the broader group of issues, called inverse problems. In this field, often pollution may result from contaminations whose origins are generated in different times and places where these contaminations have been actually found. To address such scenarios, it is necessary to develop specific techniques that allow to identify time and space features of unknown contaminant sources. The characterization of the contaminant source is of utmost importance for the planning of subsurface remediation in the polluted site. In this work, such identification is solved as an inverse problem in two stages. Firstly a Multi Layer Perceptron neural network is trained on a set of numerical simulations, and then the case under study is reconstructed by inverting the neural model.
Maria Laura Foddis; Augusto Montisci. Artificial Neural Networks Based Approach for Identification of Unknown Pollution Sources in Aquifers. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12255, 877 -890.
AMA StyleMaria Laura Foddis, Augusto Montisci. Artificial Neural Networks Based Approach for Identification of Unknown Pollution Sources in Aquifers. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12255 ():877-890.
Chicago/Turabian StyleMaria Laura Foddis; Augusto Montisci. 2020. "Artificial Neural Networks Based Approach for Identification of Unknown Pollution Sources in Aquifers." Transactions on Petri Nets and Other Models of Concurrency XV 12255, no. : 877-890.
In this paper, we discuss a simple architecture for supporting the inspection of a generic dataset using natural language queries. We show how to integrate modern Artificial Intelligence libraries in the system and how to derive chart visualization out of the user’s intent. The result is a lightweight architecture for supporting such natural language queries in web-based visualization tools. Finally, we report on the user evaluation of the interface, showing a good acceptance and effectiveness of the proposed approach.
Franscesca Bacci; Federico Maria Cau; Lucio Davide Spano. Inspecting Data Using Natural Language Queries. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12254, 771 -782.
AMA StyleFranscesca Bacci, Federico Maria Cau, Lucio Davide Spano. Inspecting Data Using Natural Language Queries. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12254 ():771-782.
Chicago/Turabian StyleFranscesca Bacci; Federico Maria Cau; Lucio Davide Spano. 2020. "Inspecting Data Using Natural Language Queries." Transactions on Petri Nets and Other Models of Concurrency XV 12254, no. : 771-782.
Territorial attractiveness to production activities is a determining factor for the revitalization of degraded, abandoned, and impoverished territories and urban areas from an economic, social and environmental point of view. A competitive territory is capable of producing wealth and economic prosperity for its citizens and, at the same time, enhancing the environment, guaranteeing the protection of natural resources and cultural heritage and encourage the joint intervention of different subjects and institutional levels. New experiences in industrial plants planning concretely demonstrate how it is possible to create production plants capable of integrating sustainable principles in planning, design and management phases. It is well recognized the possibility to pursue (according to principles and sustainability objectives) the competitiveness of the production system through localization choices capable of guaranteeing economic development, environmental protection and the involvement of different public and private subjects. Authors, in accordance to the new Lombardy Region Law (LR 18/2019) on urban regeneration, develop a Planning Support System (PSS) that leads to the study and definition of key elements for the planning of complex production-industrial system. In particular, the logical framework summarizes every steps of the planning process of productive activities on a territory. Moreover, authors present the case study related to the territorial and economic organization of Pavia Province.
Roberto De Lotto; Caterina Pietra; Elisabetta Maria Venco. Territorial Attraction for New Industrial-Productive Plants. The Case of Pavia Province. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12251, 759 -775.
AMA StyleRoberto De Lotto, Caterina Pietra, Elisabetta Maria Venco. Territorial Attraction for New Industrial-Productive Plants. The Case of Pavia Province. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12251 ():759-775.
Chicago/Turabian StyleRoberto De Lotto; Caterina Pietra; Elisabetta Maria Venco. 2020. "Territorial Attraction for New Industrial-Productive Plants. The Case of Pavia Province." Transactions on Petri Nets and Other Models of Concurrency XV 12251, no. : 759-775.
Despite the widespread opinion that the traditional finance is exclusively interested in the monetary return, in the last ten years this sector has been affected by a contamination of the public principles related to the social impacts. The global development and the spread of “win-win” financial instruments such as the Social Impact Bonds (SIBs) outlines a growing interest in making an investment that aims at generating benefits for all the subjects involved, always guaranteeing a monetary return to the private investor. The complexity of identifying the social impact sectors to be preferred, in a context characterized by different social needs, represents a critical issue in the SIBs investment. This research defines a model that can constitute a decision support tool for the public and private subjects in the preliminary phases concerning the resource allocation for a social program. The proposed algorithm allows to define a temporal priority of the social impact sectors that are simultaneously able to maximize the conveniences for all the subjects involved. Through the model, the public and private subjects will be able to determine the best allocation of financial resources according to the real social needs, contributing to an effective spread of SIBs both in Italy and abroad.
Francesco Tajani; Pierluigi Morano; Debora Anelli; Carmelo Maria Torre. A Model to Support the Investment Decisions Through Social Impact Bonds as Effective Financial Instruments for the Enhancement of Social Welfare Policies. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 12251, 941 -951.
AMA StyleFrancesco Tajani, Pierluigi Morano, Debora Anelli, Carmelo Maria Torre. A Model to Support the Investment Decisions Through Social Impact Bonds as Effective Financial Instruments for the Enhancement of Social Welfare Policies. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; 12251 ():941-951.
Chicago/Turabian StyleFrancesco Tajani; Pierluigi Morano; Debora Anelli; Carmelo Maria Torre. 2020. "A Model to Support the Investment Decisions Through Social Impact Bonds as Effective Financial Instruments for the Enhancement of Social Welfare Policies." Transactions on Petri Nets and Other Models of Concurrency XV 12251, no. : 941-951.