A framework to support human factors of automation in railway intelligent infrastructure

Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectors – water and sewage, oil and gas and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the generation of timely and relevant information about the state of any type of infrastructure asset, providing a basis for reliable decision-making. This paper reports an exploratory study to understand the concepts and human factors associated with II in the railway, largely drawing from structured interviews with key industry decision-makers and attachment to pilot projects. Outputs from the study include a data-processing framework defining the key human factors at different levels of the data structure within a railway II system and a system-level representation. The framework and other study findings will form a basis for human factors contributions to systems design elements such as information interfaces and role specifications

Robust Regression Methods For Massively Decayed Intelligence Data

Homeland Security, sponsored by governmental initiatives, has become a vibrant academic research field. However, most efforts were placed with the recognition of threats (e.g. theory) and response options. Less effort was placed in the analysis of the collected data through statistical modeling. In a field that collects more than 20 terabyte of information per minute though diverse overt and covert means and indexes it for future research, understanding how different statistical models behave when it comes to massively decayed data is of vital importance. Using Monte Carlo methods, three regression techniques (ordinary least squares, least-trimmed, and maximum likelihood) were tested against different data decay models presumed to be found in homeland security research studies in order to test whether these techniques will preserve the Type I error rate in the t-test of standardized beta. The results of these Monte Carlo simulations (sample size n=30,90,120,240,480 and 100,000 iterations) showed that the least trimmed squares method should be avoided under any circumstance due to the lack of a defined standard error, while the maximum likelihood technique should be avoided with smaller sample sizes due to the inflated Type I errors. Interestingly, although it is known that the ordinary least squares regression can be impacted by non-normality and other assumption violations, it is remarkable robust to normally distributed data that is subject to massive decay. Keywords: Homeland Security, Analysis, Data Decay, Monte Carlo, Regressio

Editorial: Bridging the gap between policy and science in assessing the health status of marine ecosystems

Human activities,both established and emerging, increasingly affect the provision of marine ecosystem services that deliver societal and economic benefits. Monitoring the status of marine ecosystems and determining how human activities change their capacity to sustain benefits for society requires an evidence-based Integrated Ecosystem Assessment approach that incorporates knowledge of ecosystem functioning and services).Although,there are diverse methods to assess the status of individual ecosystem components, none assesses the health of marine ecosystems holistically, integrating information from multiple ecosystem components. Similarly,while acknowledging the availability of several methods to measure single pressures and assess their impacts, evaluation of cumulative effects of multiple pressures remains scarce.Therefore,an integrative assessment requires us to first understand the response of marine ecosystems to human activities and their pressures and then develop innovative, cost-effective monitoring tools that enable collection of data to assess the health status of large marine areas. Conceptually, combining this knowledge of effective monitoring methods with cost-benefit analyses will help identify appropriate management measures to improve environmental status economically and efficiently. The European project DEVOTES (DEVelopment Of innovative Tools for understanding marine biodiversity and assessing good Environmental Status) specifically addressed these topics in order to support policymakers and managers in implementing the European Marine Strategy Framework Directive. Here, we synthesize our main innovative findings, placing these within the context of recent wider research, and identifying gaps and the major future challenges

Bridging the gap between policy and science in assessing the health status of marine ecosystems

Human activities, both established and emerging, increasingly affect the provision of marine ecosystem services that deliver societal and economic benefits. Monitoring the status of marine ecosystems and determining how human activities change their capacity to sustain benefits for society requires an evidence-based Integrated Ecosystem Assessment approach that incorporates knowledge of ecosystem functioning and services). Although, there are diverse methods to assess the status of individual ecosystem components, none assesses the health of marine ecosystems holistically, integrating information from multiple ecosystem components. Similarly, while acknowledging the availability of several methods to measure single pressures and assess their impacts, evaluation of cumulative effects of multiple pressures remains scarce. Therefore, an integrative assessment requires us to first understand the response of marine ecosystems to human activities and their pressures and then develop innovative, cost-effective monitoring tools that enable collection of data to assess the health status of large marine areas. Conceptually, combining this knowledge of effective monitoring methods with cost-benefit analyses will help identify appropriate management measures to improve environmental status economically and efficiently. The European project DEVOTES (DEVelopment Of innovative Tools for understanding marine biodiversity and assessing good Environmental Status) specifically addressed t hese topics in order to support policy makers and managers in implementing the European Marine Strategy Framework Directive. Here, we synthesize our main innovative findings, placing these within the context of recent wider research, and identifying gaps and the major future challenges

OPTIMIZING STOCHASTIC SUSCEPTIBILITY MODELLING FOR DEBRIS FLOW LANDSLIDES: MODEL EXPORTATION, STATISTICAL TECHNIQUES COMPARISON AND USE OF REMOTE SENSING DERIVED PREDICTORS. APPLICATIONS TO THE 2009 MESSINA EVENT.

Il presente lavoro di ricerca è stato sviluppato al fine di approfondire approcci metodologici nell'ambito della sucscettibilità da frana. In particolare, il tema centrale della ricerca è rappresentato dal tema specifico dell'esportazione spaziale di modelli di suscettibilità nell'area mediterranea. All'interno del topic specifico dell'esportazione di modelli predittivi spaziali sono state approfondite tematiche relative all'utilizzo di differenti algoritmi o di differenti sorgenti, derivate da DEM o da coperture satellitari.The present work has been developed in order to enhance current methodological approaches within the big picture of the landslide susceptibility. In particular, the central topic was the spatial exportation of landslide susceptibility models within the Mediterranean sector. Within the specific subject pertaining to the spatial exportation of predictive models, different algorithms as well as different data sources have been tested. Data sources experiments assessed the integration of DEM- and remotely sensed- derived parameters in order to improve the landslide prediction

Lur labainketen analisirako hurbilketa metodologikoa eskala erregionalean: Datuen bilketa, suszeptibilitate modeloak eta euri prezipitazioen atalaseak. Gipuzkoako Lurralde Historikoan aplikatua (Euskal Herria).

227 p.Lurraldearen zonazioa lur labainketak jasotzeko aukeren arabera, suszeptibilitate mapen bitartez hain zuzen ere, hauek eragindako kalteak arindu eta mehatxua eta arrisku maila ebaluatu ahal izateko oinarrizko pausoa da. Tesi honek bide-orri baten definizioa aurkezten du, hutsetik abiatuta, lurraldearen suszeptibilitate mapen garapenerako eskala erregionalean. Helburua ikuspegi metodologiko eguneratu bat zehaztea da, prozeduraren pauso bakoitzean hartutako erabakia zientifikoki justifikatuak eta onartua izan daitezen. Hainbat esperimentu eta aplikazio gauzatzeko Gipuzkoako Probintzia hautatu da (1980 km2) . Ezaugarri eta izaera desberdineko hainbat aldagai independente, mota eta iturri desberdineko lur labainketa inbentarioak eta metodo ezagun nahiz metodo berritzaileekin batera ikuspegi desberdinak jorratu dira, azkenean lan honek aurkezten dituen ondorioak lortzeko.Emaitzen arabera, inferentzia geomorfologikoaren beharra azpimarratu daiteke estatistikoki gidatutako arauen arabera aldagai independenteen hautaketa egiterako orduan, hala nola, aldagai kategorikoen transformatzea aldagai jarraietan suszeptibilitate-modeloak garatzerako orduan onuragarria dela ere ondorioztatu da. Gainera, lur labainketen suszeptibilitate modeloak kalibratzeko ikuskatutako eremu efektiboaren erabilera positiboa dela frogatu da, lur labainketen inbentarioa landa lanaren bitartez eskuratu den kasuetan. Bestalde, malda unitateen erabilerak lurralde unitate bezala, ohikoak diren pixel unitateak izan beharrean, landa laneko inbentario batek ezarri dezakeen ziurgabetasuna arintzeko ahalmena erakutsi du.Horretaz gain, lur labainketak gertatzeko beharrezko prezipitazio atalasa definitzeko algoritmo baten aplikazioak ikerketa eremu berberean, aurreikuspenak egiteko beharrezkoa den informazioa erakutsi du, alerta goiztiar sistema baterantz aurreratzen joateko dauden aukerak goraipatuz

EUSN 2021 Book of Abstracts, Fifth European Conference on Social Networks

Book of abstract of the fifth European conference on Social Networks EUSN 202