100 research outputs found
Evaluating results of public sector reforms in Rechtsstaat countries: the role of context and the role of processes in the reform of the Italian and French cultural heritage system.
No full textThis paper analyses the results of public management reform in Italy focusing on its managerial
significance in the field of cultural heritage. The primary aim is to overcome the general lack of
studies analysing the impact of managerial reforms in governments with a Rechtsstaat tradition and
to understand if, besides the political and institutional context characterised by a highly legalistic
system there are other important factors that might affect results of reforms. Through an in-depth
analysis of the reform of the Italian Ministry and a comparison with the French museum sector, the
paper demonstrates that the way in which the process of change is managed significantly affects the
results of reform. Specifically the author affirms that in order to obtain good reform results a greater
active involvement of senior bureaucrats in the process of designing reforms is necessary
Abstract Data Types for Spatio-Temporal Remote Sensing Analysis (Short Paper)
No full textAbstract data types are a helpful framework to formalise analyses and make them more transparent, reproducible and comprehensible. We are revisiting an approach based on the space, time and theme dimensions of remotely sensed data, and extending it with a more differentiated understanding of space-time representations. In contrast to existing approaches and implementations that consider only fixed spatial units (e.g. pixels), our approach allows investigations of the spatial units' spatio-temporal characteristics, such as the size and shape of their geometry, and their relationships. Five different abstract data types are identified to describe geographical phenomenon, either directly or in combination: coverage, time series, trajectory, composition and evolution
Mediation Analysis with Survival Outcomes: Accelerated Failure Time Versus Proportional Hazards Models
No full textObjective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration.Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings.Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome – underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG.Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results
A Science Mapping Review of Human and Organizational Factors in Structural Reliability
No full textIn the structural safety field, it is widely acknowledged that human error is the major contributor to structural failure. Since Human and Organizational Factors (HOFs) are critical latent conditions that can lead to human errors and further structural failures, it is essential to study into HOFs in the building industry to prevent the occurrence of failures. In this research, a bibliometric review of the existing literature on HOFs influencing structural reliability was conducted and results have been visualized in science maps. Insights into the publication output and trend, the key topics and its evolvement over time, the publication sources, as well as the contributing academics and their collaborations have been gained from the science mapping review. Apart from this, HOFs were collected from literature, after which a meta-analysis has been performed to identify the critical factors for structural reliability. In conclusion, this review provides a holistic picture of the current status for studies concerning HOFs influencing structural reliability and outlines the possible critical HOFs identified by existing research.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Safety and Security ScienceApplied Mechanic
The LAM Dataset: A Novel Benchmark for Line-Level Handwritten Text Recognition
No full textHandwritten Text Recognition (HTR) is an open problem at the intersection of Computer Vision and Natural Language Processing. The main challenges, when dealing with historical manuscripts, are due to the preservation of the paper support, the variability of the handwriting – even of the same author over a wide time-span – and the scarcity of data from ancient, poorly represented languages. With the aim of fostering the research on this topic, in this paper we present the Ludovico Antonio Muratori (LAM) dataset, a large line-level HTR dataset of Italian ancient manuscripts edited by a single author over 60 years. The dataset comes in two configurations: a basic splitting and a date-based splitting which takes into account the age of the author. The first setting is intended to study HTR on ancient documents in Italian, while the second focuses on the ability of HTR systems to recognize text written by the same writer in time periods for which training data are not available. For both configurations, we analyze quantitative and qualitative characteristics, also with respect to other line-level HTR benchmarks, and present the recognition performance of state-of-the-art HTR architectures. The dataset is available for download at https://aimagelab.ing.unimore.it/go/lam
A Systematic Approach to Improve Reliability of Storm Surge Barrier Closures
No full textCoastal defenses must be upgraded to combat increasing flood risk due to climate change and other factors. Storm surge barriers, large movable hydraulic structures that close temporarily during storm surges to prevent coastal floods, play a vital role in protecting estuaries. Due to the complexity of their risk analyses, important improvements are sometimes overseen. Our objective is to develop a systematic approach which is more likely to find these important improvements. We tested the method to three historic cases where important improvements were initially overlooked. We anticipate that our method can be applied to other safety systems with a large number of failure modes as well.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Hydraulic Structures and Flood Ris
Learning to Read L'Infinito: Handwritten Text Recognition with Synthetic Training Data
No full textDeep learning-based approaches to Handwritten Text Recognition (HTR) have shown remarkable results on publicly available large datasets, both modern and historical. However, it is often the case that historical manuscripts are preserved in small collections, most of the time with unique characteristics in terms of paper support, author handwriting style, and language. State-of-the-art HTR approaches struggle to obtain good performance on such small manuscript collections, for which few training samples are available. In this paper, we focus on HTR on small historical datasets and propose a new historical dataset, which we call Leopardi, with the typical characteristics of small manuscript collections, consisting of letters by the poet Giacomo Leopardi, and devise strategies to deal with the training data scarcity scenario. In particular, we explore the use of carefully designed but cost-effective synthetic data for pre-training HTR models to be applied to small single-author manuscripts. Extensive experiments validate the suitability of the proposed approach, and both the Leopardi dataset and synthetic data will be available to favor further research in this direction
New Guidelines for the Quality Control of Risk Analyses of Critical Hydraulic Structures
No full textThe efficacy of risk models and risk analyses critically hinges on sufficient model evaluation. Nevertheless, the usefulness for the intended purpose is rarely systematically assessed. Poor or even lacking model evaluation of the applied risk models and analyses also troubles the asset management of storm surge barriers in the Netherlands. In practice, obvious flaws, missing failure modes and use that deviates from the original purpose regularly lead to unpleasant surprises, unnecessary costs and avoidable risks.Here, we introduce new guidelines for the quality control during the development, testing, maintenance and usage of risk analyses of critical hydraulic structures.First responses among stakeholders are rather positive since the guidelines help modelers and analysts to better understand critics and independent reviewers to structure their comments. However, the efficacy of the guidelines itself also need rigorous evaluation in the coming years. This may prove challenging as the application of the guidelines may also reveal that the organizations that operation the storm surge barriers are currently insufficiently equipped for the rigorous quality control of risk models and risk analyses.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Hydraulic Structures and Flood Ris
A Copula-Based Bayesian Network to Model Wave Climate Multivariate Uncertainty in the Alboran Sea
No full textAn accurate estimation of wind and wave variables is key for coastal and offshore applications. Recently, copulas have gained popularity for modelling wind and waves multivariate dependence, since accounting for the hydrodynamic relationships between them is needed to ensure reliable estimations of the required design values. In this study, copula-based Bayesian networks (BNs) are explored as a tool to model extreme values of significant wave height (Hs), wave period, wave direction, wind speed and wind direction. The model is applied to a case study located in the Alboran sea, close to the Spanish coast, using ERA5 database. Extreme values of Hs are sampled using Yearly Maxima and concomitant values of the missing variables are used. K-means clustering algorithm is applied to separate the different wave components and a BN is built for each of them. The assumption of modelling the dependence between the variables using Gaussian copulas and the structure of BNs are supported with the d-calibratioson score. Fitted marginal distributions are introduced in the nodes of the BNs and their performance is assessed using in-sample data and the coefficient of determination. The BN models proposed present high performance with a low computational cost proving to be powerful tools for modelling the variables under investigation. Future research will include different locations and databases.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Hydraulic Structures and Flood Ris
Schematizing Rainfall Events with Multivariate Depth-Duration Dependence
No full textAccurately modelling rainfall events is crucial for flood risk assessment and stormwater infrastructure design. However, transforming statistical characteristics of events into relevant rainfall patterns is challenging due to the natural variability of rainfall. Two commonly used methods to schematize rainfall events have limitations: the nested storm profile overestimates the resulting flow by assuming complete dependence between different durations, while determining the critical event duration by simulating each duration separately assumes independence and underestimates the flow. To overcome these limitations, this study presents a method that models the dependence between different rainfall durations using a Gaussian copula and combines this with marginal rain statistics to create a probabilistic model for the rain event. The SCS Curve Number approach is used to model the resulting flow, and a first-order reliability method (FORM) is applied to determine the critical combination of durations within an event. The findings of this study show that the rainfall events generated using the proposed method result in comparable flows to those produced by conventional design events. While this may not make the model a preferred choice for standard applications, it can still be valuable for flood risk assessments as it provides a probabilistic model that better captures critical rainfall patterns.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Hydraulic Structures and Flood Ris
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