1,721,027 research outputs found
Florence : the churches, the palaces, the treasures of art : a handbook for students and travellers
No full textPrecede ó tít.: "Wonders of Italy"Mención de ed. lit. sacado de prelimNa antep.: "Florence : the city of flowers"826 i
A novel approach for detecting alerts in urban pollution monitoring with low cost sensors
No full textThe problem of estimating the pollutants in urban areas is one of the most active research in recent years due to the increasing concerns about their influence on human health. Solide state sensors, increasingly small and inexpensive, are being used to build compact multisensor devices. Suffering from sensors instabilities and cross-sensitivities, they need ad-hoc calibration procedures in order to reach satisfying performance levels. In this paper we propose a novel approach based on Nonlinear AutoRegressive eXogenous model (NARX) to estimate pollutants in urban area and detecting alerts with respect to law limits. We compared our proposal with two other techniques, based on a Feed Forward Neural Network and a Semi Supervised Learning approach, respectively. Numerical simulations have been carried out to validate the proposed approach on a real dataset. © 2013 IEEE
Evaluation and design of a rain gauge network using a statistical optimization method in a severe hydro-geological hazard prone area
No full textRainfall data collection gathered in continuous by a distributed rain gauge network is instrumental to more effective hydro-geological risk forecasting and management services though the input estimated rainfall fields suffer from prediction uncertainty. Optimal rain gauge networks can generate accurate estimated rainfall fields. In this research work, a methodology has been investigated for evaluating an optimal rain gauges network aimed at robust hydrogeological hazard investigations. The rain gauges of the Sarno River basin (Southern Italy) has been evaluated by optimizing a two-objective function that maximizes the estimated accuracy and minimizes the total metering cost through the variance reduction algorithm along with the climatological variogram (time-invariant). This problem has been solved by using an enumerative search algorithm, evaluating the exact Pareto-front by an efficient computational time. © 2017 Author(s)
Online anomaly detection on rain gauge networks for robust alerting services to citizens at risk from flooding
No full textThe modern cities are addressing their innovation efforts for facing not just the common stresses cities accumulate daily, but also the sudden shocks can occur such as urban floods. Networked gauge stations are instrumental to robust floods alerts though they suffer from error and fault. For capturing the anomalous behavior of networked rain gauges, the use of an online anomaly detection methodology, based on the Support Vector Regression (SVR) technique, has here been investigated and developed. The specific anomaly case of incorrectly zero sensor readings has been efficiently addressed by a centralized architecture and a prior-knowledge free approach based on SVRs that simulate the normality profile of the networked rain gauges, on the basis of the spatial-temporal correlation existing among the observed rainfall data. Real data from the pilot rain gauge network deployed in Calabria (South Italy) have been used for simulating the anomalous sensor readings. As a result, we conclude that SVR-based anomaly detection on networked rain gauges is appropriate, detecting the eventual rain gauge fault effectively during the rainfall event and by passing through increased alert states (green, yellow, orange, red). © Springer International Publishing AG 2017
A new SMAA-based methodology for incomplete pairwise comparison matrices: Evaluating production errors in the automotive sector
No full textAnalysing and mitigating errors in production processes is a primary objective of companies in the automotive sector. Unfortunately, due to inaccurate or partially missing information, comparing errors is often very difficult, resulting from the experts’ provision of incomplete pairwise comparison matrices. In the literature, several techniques have been developed to complete such matrices. These techniques merely estimate what the decision makers or experts would have entered according to known entries. In this article, we propose a new methodology based on the stochastic multi-objective acceptability analysis; we apply it to vary the missing entries of the pairwise comparison matrix, thus providing the probability that an alternative/criterion will attain a given rank. This approach gives a complete view of the possible outcomes because it represents all possible decision maker mindsets. We present a case study carried out in a multinational automotive industry where we apply our methodology for evaluating errors in the production process
Sulla stima del traporto solido in sospensione in corsi d’acqua naturali in funzione di parametri geomorfici
No full textLa memoria considera un metodo di regressione, che prevede quali variabili indipendenti assegnati parametri geomorfici, per la stima della massa media annuale di trasporto solido in sospensione in una sezione fluviale. In dettaglio, viene utilizzato un modello di regressione messo a punto da Ciccacci et al. (1987), che è stato calibrato su dati relativi a 20 bacini idrografici italiani e nel quale le variabili indipendenti sono la densità di drenaggio e l’indice di anomalia gerarchica della rete idrografica. Il modello è applicato ad un piccolo bacino localizzato in Abruzzo, per il quale è possibile confrontare le stime ottenute di trasporto solido in sospensione con dati di interrimento di piccoli invasi artificiali. I risultati confermano l’attendibilità del metodo, sebbene emerga la necessità di ulteriori indagini per supportarne l’applicazione a bacini di piccola estensione
Checking consistency for Group-PAHP: a case study of tourism facilities in COVID-19 pandemic
No full textThe pandemic situation due COVID-19 highlighted a great vulnerability of tourism systems in the world, defined a scenario characterized by strong uncertainties, unfavorable prospects and widespread fragility (Michie 2020). Our work proposes the use of Multi-Criteria Decision Aiding (MCDA) for analyzing the potentiality of local territory development through the improvement of the tourism facilities. More precisely, we propose the use of the Parsimonious AHP (Abastante et al. 2019) for group choices to analyze a decision-making problem for the improvement of tourism facilities. As the complexity of the decision-making problem and the number of decision-makers grow, there may be problems of consistency of judgments and therefore problems of consistency of the matrices (Brunelli and Cavallo 2020a). Consistency is difficult to achieve in the real situation (Maturo et al. 2005). Our work aims to verify in a 4-step process the errors of consistency that occurs in Pairwise Comparison Matrices with the use of Parsimonious AHP for group choices. Furthermore, we propose a new innovative tool for decision makers to tackle complex problems, with multiple decision categories, a large number of alternatives and several criteria
Using Electre to analyze the behaviour of economic agents.
No full textAccording to behavioural finance, economic agents display cognitive bias, heuristics and emotional factors that generate
preferences which systematically violate the rationality assumptions of the normative model of classical decision theory.
Rather than maximizing the expected utility, representing the optimal choice, they attempt to accept a satisfactory solution.
Morton and Fasolo (J Oper Res Soc 60:268–275, 2009) outlined some behavioural findings relevant to the practice of
multicriteria approach. In this paper, we propose a multicriteria model for analysing some experiments proposed by
Kahneman and Tversky (Econometrica 47:263–29 l, 1979). Our aim is to verify whether a multicriteria tool reduces or
minimizes cognitive biases. We focus on ELECTRE due to its main features: it accepts the violation of some mathematical
axioms. By a simulation study, we represent a set of prospects by means of decision matrices: the prospects are considered
as alternatives, the events as criteria, the probabilities of events as the weights assigned to criteria. Then, we apply
ELECTRE to verify whether the preference ranking among the alternatives confirms the results obtained by Kahneman–
Tversky, that is, whether it is able to describe the emotional behaviours of economic agents
Applying numerical models and optimized sensor networks for drinking water quality control
No full textDrinking water distribution networks must provide safe water to the consumers in adequate quantity and quality. In this framework, the present research work investigates an integrated approach for drinking water quality control by applying hydraulic and water quality models to a real aqueduct. The results of the model simulations allow identifying the optimal locations of monitoring stations in order to achieve an effective contaminant detection, and to ensure the maximum protection of the consumers health. The methodology is applied to a case study, referring to a real aqueduct located in Campania (South Italy). © 2015 Published by Elsevier Ltd
A Sensor Fusion Method Applied to Networked Rain Gauges for Defining Statistically Based Rainfall Thresholds for Landslide Triggering
No full textTimely alerts provided to the communities at risk of landslides can prevent casualties and costly damages to people, buildings and infrastructures. The rainfalls are one of the primary triggering causes for landslides so that empirical approaches based on the correlation between landslides occurrence and rainfall characteristics, are considered effective for warning systems. This research work has intended to develop a landslide alerting system by using a Sensor Fusion method based on the SVC (Support Vector Classification) techniques. This method fuses rainfall data gathered in continuous by networked rain gauges and returns confidence degrees associated to the not occurrence of the landslide event as well as to the occurrence of one. By using a k-fold validation technique, an SVC-model, with AUC (Area Under the Curve) mean of 0,964733 and variance of 0,001243, has been defined. The proposed method has been tested on the regional rain gauges network, deployed in Calabria (Italy). © Springer International Publishing AG 2018
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