Alessandro Pagano

A Bayesian vulnerability assessment tool for drinking water mains under extreme events

Drinking water security is a life safety issue as an adequate supply of safe water is essential for economic, social and sanitary reasons. Damage to any element of a water system, as well as corruption of resource quality, may have significant effects on the population it serves and on all other dependent resources and activities. As well as an analysis of the reliability of water distribution systems in ordinary conditions, it is also crucial to assess system vulnerability in the event of natural disasters and of malicious or accidental anthropogenic acts. The present work summarizes the initial results of research activities that are underway with the intention of developing a vulnerability assessment methodology for drinking water infrastructures subject to hazardous events. The main aim of the work was therefore to provide decision makers with an effective operational tool which could support them mainly to increase risk awareness and preparedness and, possibly, to ease emergency management. The proposed tool is based on Bayesian Belief Networks (BBN), a probabilistic methodology which has demonstrated outstanding potential to integrate a range of sources of knowledge, a great flexibility and the ability to handle in a mathematically sound way uncertainty due to data scarcity and/or limited knowledge of the system to be managed. The tool was implemented to analyze the vulnerability of two of the most important water supply systems in the Apulia region (southern Italy) which have been damaged in the past by natural hazards. As well as being useful for testing and improving the predictive capabilities of the methodology and for possibly modifying its structure and features, the case studies have also helped to underline its strengths and weaknesses. Particularly, the experiences carried out demonstrated how the use of BBN was consistent with the lack of data reliability, quality and accessibility which are typical of complex infrastructures, such as the water distribution networks. The potential applications and future developments of the proposed tool have been also discussed accordingly.

Adaptive learning: A new approach in student modeling

Here is described the implementation of adaptivity in Moodle: a specific but very common Learning Management System. After a preliminary study about the adaptive built-in features in moodle learning management system, and the capabilities ready to perform a suitable student modeling, the research team extended Moodle capabilities with a specific data model, student model and tutoring engine to perform automatic monitoring and sequencing of learning objects for each particular learner. The future implementation of this project is related to testing activities in order to prove the efficiency method in content and course delivery.

Modelling the complexity of the network of interactions in flood emergency management: The Lorca flash flood case

Abstract There is growing awareness that fast response to emergency situation requires effective coordination among several institutional and non-institutional actors. The most common approaches, based on innovating technologies for information collection and management, are not sufficient to cope with the increasing complexity of emergency management. This work demonstrates that effective cooperation claims for a shift from information management to interaction management. Therefore, methods and tools are required in order to better understand the complexity of the interactions taking place during an emergency, and to analyse the actual roles and responsibilities of the different actors. This paper details the design and implementation of an integrated approach aiming to unravel the complexity of the interaction network based on Storytelling, the Problem Structuring Method, and Social Network Analysis. The potential of the integrated approach has been investigated in the Lorca (Spain) flood risk management case study.

Head loss coefficient of orifice plate energy dissipator

The authors have presented a numerical and experimental study on the hydraulic behaviour of a single-hole orifice, finding that the loss coefficient and the recirculation length are influenced by the contraction ratio β = d/D and the relative orifice thickness α. This is interesting, because nowadays not all the aspects of orifice hydraulics are clarified, particularly the effects of orifice geometry on the efficiency and cavitation behaviour. Fratino (2000) and Malavasi et al. (2010) experimentally studied the hydraulic performance of perforated plates, both for singleand multi-hole orifices, finding a relevant effect on the loss coefficient due to the plate geometry, related to the relative plate thickness l̄ = s/dh as the ratio between plate thickness and hole diameter. For thick-edged orifices (l̄ > 0.015), and fully-developed approach flow of Reynolds number R = VD/ν > 105, where V = mean approach flow velocity, D = pipe diameter, ν = kinematic viscosity, Idelchik (1994) proposed for the loss coefficient ξ

Emergency Management of Drinking Water Infrastructures Based on a Bayesian Decision Support System

The present work summarizes the theoretical development process and the preliminary results of a research activity oriented to the definition of a Decision Support System (DSS) to be used for managing drinking water systems exposed to different hazard classes. The core of such DSS is a probabilistic vulnerability assessment tool based on Bayesian Belief Networks, mainly developed integrating expert knowledge and literature information. This vulnerability assessment tool proved able to define a reliable map of vulnerability levels for complex and interconnected infrastructures, thus helping decision-makers in the selection of the optimal strategies to respond to emergencies. The DSS is based also on the implementation of hydraulic models, both for gravity and pressurized water mains, which should provide information regarding the changes in the hydraulic behavior of the network due to a specific event or an action. A case study is described, confirming the potentialities of the proposed tool.

An Open Source LMS Vision and Development. The Development of Innovative Web Technologies for E-Learning: The eLearning Portal Project

The aim of the project is the development of an inn ovative, Open Source-based eLearning portal, which provides high scalability and versatility, as well as it is easy to upgrade; it aims at meeting some changeable requirement in the field of distanc e learning (yearly or even monthly innovation). The modular structure and flexibility provided by t he portal makes this system adaptable to any kind of educational and/or academic situation, allo wing also the development in step with innovative and specific Web Technologies. The project has been developed thanks to the experi ence obtained in managing a postgraduate specialization course promoted by University of Bar i (www.comedudida.org ) and it keeps developing as suitable tools for proper online form ation are designed. This experience has been studied inside the OSEL research project by Univers ty of Bari (www.osel.it).

Dealing with Uncertainty in Decision-Making for Drinking Water Supply Systems Exposed to Extreme Events

The availability and the quality of drinking water are key requirements for the well-being and the safety of a community, both in ordinary conditions and in case of disasters. Providing safe drinking water in emergency contributes to limit the intensity and the duration of crises, and is thus one of the main concerns for decision-makers, who operate under significant uncertainty. The present work proposes a Decision Support System for the emergency management of drinking water supply systems, integrating: i) a vulnerability assessment model based on Bayesian Belief Networks with the related uncertainty assessment model; ii) a model for impact, and related uncertainty assessment, based on Bayesian Belief Networks. The results of these models are jointly analyzed, providing decision-makers with a ranking of the priority of intervention. A GIS interface (G-Net) is developed to manage both input spatial information and results. The methodology is implemented in L’Aquila case study, discussing the potentialities associated to the use of the tool dealing with information and data uncertainty.

Evaluation of Student Performance in Adaptive E-Learning Processes with Active Tutorship

This paper describes the implementation of adaptive technology in a specific, Open Source, Learning Management System (LMS). After a preliminary study about the adaptive features already built-in and the capabilities ready to perform a suitable student modeling, the research team extended those capabilities with a specific data model, student model, and tutoring engine to perform automatic monitoring and sequencing of Learning Objects for each particular learner. Testing activities has proven the efficiency method in content and course delivery and given the opportunity to further develop a predicting tool based on data mining student modeling. This provides an efficient tool in tutorship activities. This paper describes some best practices developed during a Tempus IV Project granted by EU.

Data Mining Methods to Assess Student Behavior in Adaptive e-Learning Processes

How could data mining help the development of e-learning methodologies? How could an instructional designer take benefit from the use of adaptive learning? How could adaptive learning be implemented in an Open Source platform? In this paper will be described the implementation of adaptivity technology in a specific, Open Source, Learning Management System (LMS). After a preliminary study about the adaptive features already built-in and the capabilities ready to perform a suitable student modeling, the research team extended those capabilities with a specific data model, student model and tutoring engine to perform automatic monitoring and sequencing of Learning Objects for each particular learner. The future implementation of this project is related to testing activities in order to prove the efficiency method in content and course delivery. This paper describes some best practices developed during a Tempus IV Project granted by EU.

Integrating “Hard” and “Soft” Infrastructural Resilience Assessment for Water Distribution Systems

Cities are highly dynamic systems, whose resilience is affected by the interconnectedness between “hard” and “soft” infrastructures. “Hard infrastructures” are the functional networks with physical elements providing goods or services. “Soft infrastructures” (culture, governance, and social patterns) encompass the social networks, make the hard infrastructures work, and are vital for understanding the consequences of disasters and the effectiveness of emergency management. Although the dynamic interactions between such infrastructures are highly complex in the case of the occurrence of hazardous events, it is fundamental to analyze them. The reliability of hard infrastructures during emergency management contributes to keep alive the social capital, while the community, its networks, and its own resilience influence the service provided by infrastructural systems. Resilience-thinking frameworks overcome the limits of the traditional engineering-oriented approaches, accounting for complexity of socio-technical-organizational networks, bridging the static and dynamic components of disasters across pre- and postevent contexts. The present work develops an integrated approach to operatively assess resilience for the hard and soft infrastructural systems, aiming at modeling the complexity of their interaction by adopting a graph theory-based approach and social network analysis. The developed approach has been experimentally implemented for assessing the integrated resilience of the hard/soft infrastructures during the L’Aquila 2009 earthquake.