102,690 research outputs found

    Automatic fault identification in sensor networks based on probabilistic modeling

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    This work proposes a mechanism able to automatically categorize different types of faults occurring in critical infrastructures and especially water distribution networks. The mechanism models the relationship exhibited among the sensor datastreams based on the assumption that its pattern alters depending on the fault type. The first phase includes linear time invariant modeling which outputs a parameters vector. At the second phase the evolution of the parameter vectors is captured via hidden Markov modeling. The methodology is applied on data coming from the water distribution network of the city of Barcelona. The corpus contains a vast amount of data representative of nine network states. The nominal is included for enabling fault detection. The achieved classification rates are quite encouraging and the system is practical

    Coherent Risk Measures Under Filtered Historical Simulation

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    Recent studies have strongly criticised conventional VaR models for not providing a coherent risk measure. Acerbi provides the intuition for an entire family of coherent measures of risk known as "spectral risk measures" [Spectral measures of risk: A coherent representation of subjective risk aversion. Journal of Banking and Finance 26 (7) (2002) 1505-1518]. In this study we illustrate how the Filtered Historical Simulation [Barone-Adesi, G., Bourgoin, F., Giannopoulos, K., 1998. Don't look back. Risk 11, 100-104; Barone-Adesi, Giannopoulos, K., Vosper, L., 1999. VaR without correlations for non-linear portfolios. Journal of Futures Markets 19, 583-602], can provide an improved methodology for calculating the Expected Shortfall. Thereafter, we prove that these new risk measures are spectral and are coherent as well, following Acerbi. Furthermore, we provide the statistical error formula that allows to calculate the error for our model

    Faults and Cyber Attacks Detection in Critical Infrastructures

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    The explosive growth of the Internet has introduced advanced services facilitating our every day life. On the other hand it created increased dependence on computer systems which may be seen as an additional source of vulnerability to disruption scenarios due to both physical and cyber-based incidents. In this paper we study the case of Critical Infrastructures (CIs), and especially power grid systems, which is one of the variety of services that nowadays relies on computers and the Internet for its operation. We design an experimental platform consisting of a power grid simulator and a cyber network emulator. This paper proposes a combinatorial method for automatic detection and classification of faults and cyber-attacks occurring on the power grid system when there is limited data from the power grid nodes due to cyber implications. The efficiency of the proposed method is demonstrated via an extensive experimental phase measuring the false positive rate, false negative rate and the delay of the detections.JRC.E.2 - Technology Innovation in Securit

    Supplemental Material - Embolic protection devices for carotid artery stenting: A network meta-analysis

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    Supplemental Material for Embolic protection devices for carotid artery stenting: A network meta-analysis by Stefanos Giannopoulos, Marios Sagris, Spyridon Giannopoulos, Andreas Tzoumas, Damianos G Kokkinidis, Pavlos Texakalidis, George Koutsias, Panagiotis Volteas, Li Jing, and Rafael D Malgor in Vascular</p

    Modeling interdependencies in multi-sectoral critical infrastructure systems: Evolving the DMCI approach

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    The adequate functioning of critical infrastructures is crucial for sustaining the development of today's societies and economies. It is a priority, therefore, to foster our understanding of such systems and ability to assess interdependencies, vulnerabilities, and resilience. Starting from the DMCI (Dynamic functional Modelling of vulnerability and interoperability of Critical Infrastructure systems) framework proposed in [1], in this paper we present an evolved formalism (DMCI-e). This introduces novel modeling features and enhances applicability while keeping the original focus on a dynamic and network-centric characterization of disservice. A key objective is to respond to the need, expressed by policy-makers and critical infrastructure regulators, for sector-agnostic and multi-granular infrastructure models for the estimation of service supply capabilities and response during and after disruptive events

    GeoAR A calibration method for Geographic-aware augmented reality: Getting started

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    &lt;h2&gt;How to cite&lt;/h2&gt; &lt;p&gt;Please, don't forget to cite the original research article that result in this application:&lt;/p&gt; &lt;p&gt;Galv&atilde;o, M. L., Fogliaroni, P., Giannopoulos, I., Navratil, G., Kattenbeck, M., &amp; Alinaghi, N. (2024). &lt;a href="https://www.tandfonline.com/doi/full/10.1080/13658816.2024.2355326"&gt;&lt;strong&gt;GeoAR: a calibration method for Geographic-Aware Augmented Reality&lt;/strong&gt;&lt;/a&gt;. &lt;em&gt;International Journal of Geographical Information Science&lt;/em&gt;, 1&ndash;27. &lt;a href="https://doi.org/10.1080/13658816.2024.2355326"&gt;https://doi.org/10.1080/13658816.2024.2355326&lt;/a&gt;&lt;/p&gt; &lt;h2&gt;GeoAR getting started application&lt;/h2&gt; &lt;p&gt;This getting started tutorial provides the basic information so you can implement your own geographic-aware AR application.&lt;/p&gt; &lt;p&gt;The project we provide here is described in the IJGIS article GeoAR: A calibration method for Geographic-aware augmented reality, and it provides the means for all four calibration approaches described in the article.&lt;/p&gt; &lt;p&gt;The set-up we provide here is for the device Microsoft Hololens 2, but feel free to adpat the code to use in different devices.&lt;/p&gt; &lt;h2&gt;&lt;strong&gt;Basic requirements&lt;/strong&gt;&lt;/h2&gt; &lt;p&gt;In order to run and develop your GeoAR application using this project it is required the following:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;AR device (Microsoft Hololens 2)&lt;/li&gt; &lt;li&gt;Unity Hub with Unity 2021.3.2f1 installed (adaptations for a later version of Unity might be necessary)&lt;/li&gt; &lt;li&gt;Microsoft Visual Studio (Version 16.11.15 or later)&lt;/li&gt; &lt;li&gt;Mixed Reality Toolkit (MRTK) foundation package for Unity (2.8.0.0)&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;If you do not have experience in developing with Unity or MRTK, we highly recommend you go through the following Microsoft training modules:&lt;/p&gt; &lt;p&gt;&lt;a href="https://learn.microsoft.com/en-us/training/modules/learn-mrtk-tutorials/1-1-introduction"&gt;Introduction to the Mixed Reality Toolkit &ndash; Set Up Your Project and Use Hand Interaction&lt;/a&gt;&lt;/p&gt; &lt;p&gt;&lt;a href="https://learn.microsoft.com/en-us/training/modules/intro-to-mixed-reality/"&gt;Introduction to mixed reality&lt;/a&gt;&lt;/p&gt; &lt;h2&gt;&lt;strong&gt;1. Download and &lt;/strong&gt;open&lt;strong&gt; &lt;/strong&gt;the &lt;strong&gt;project in Unity&lt;/strong&gt;&lt;/h2&gt; &lt;ol&gt; &lt;li&gt;Download the project folder and unpack it in your local machine&lt;/li&gt; &lt;li&gt;Use Unity Hub to open the project folder GeoARUnityProject (make sure you have the right version installed)&lt;/li&gt; &lt;li&gt;If everything is correct, you will be able to play the application in the game mode.&lt;/li&gt; &lt;/ol&gt; &lt;p&gt;Further instructions with video tutorials can be found here :&lt;/p&gt; &lt;p&gt;&lt;a href="https://geoinfo.geo.tuwien.ac.at/geoar-getting-started/"&gt;https://geoinfo.geo.tuwien.ac.at/geoar-getting-started/&lt;/a&gt;&lt;/p&gt; &lt;h3&gt;&lt;strong&gt;License&lt;/strong&gt;&lt;/h3&gt; &lt;p&gt;All data is published under the CC-BY 4.0 license. The code is under the GNU General public license&lt;/p&gt

    Developments in transport telematics applications in Japan: traffic management, freight and public transport

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    This paper summarizes a report on Japanese transport telematics written as a result of a contract between the authors and DG XIII of the Commission of the European Union. The assignment principally covered freight transport and urban traffic management, but the work extended in other fields as well. As part of this work, we organized a technical tour in Japan during which we had meetings and visited a number of key Japanese establishments and experts who informed us about the state-of-the-art and current thinking. Previous missions had established a fairly good knowledge of the state of affairs in Japan in other areas. Freight transport (and to a certain extent public transport) were the main areas where information was scarce. Any comments or recommendations in this report are those of the authors themselves and do not express official EC views

    18-0034_supplementary_tables – Supplemental material for Effect of Open- vs Closed-Cell Stent Design on Periprocedural Outcomes and Restenosis After Carotid Artery Stenting: A Systematic Review and Comprehensive Meta-analysis

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    Supplemental material, 18-0034_supplementary_tables for Effect of Open- vs Closed-Cell Stent Design on Periprocedural Outcomes and Restenosis After Carotid Artery Stenting: A Systematic Review and Comprehensive Meta-analysis by Pavlos Texakalidis, Stefanos Giannopoulos, Damianos G. Kokkinidis and Giuseppe Lanzino in Journal of Endovascular Therapy</p

    A fault diagnosis system for interdependent critical infrastructures based on HMMs

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    This paper proposes a probabilistic modeling scheme for analyzing malicious events appearing in interdependent critical infrastructures. The proposed scheme is based on modeling the relationship between two datastreams by means of a hidden Markov model (HMM) trained on the parameters of linear time-invariant dynamic systems which estimate the relationships existing among the nodes of the network over consecutive time windows. Our study includes an energy network (IEEE 30 model bus) operated via a telecommunications infrastructure. The relationships among the elements of the network of infrastructures are represented by an HMM and the novel data is categorised according to its distance (computed in the probabilistic space) from the training ones. We considered two types of cyber-attacks (denial of service and integrity/replay) and report encouraging results in terms of false positive rate, false negative rate and detection delay.JRC.G.5 - Security technology assessmen
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