1,720,954 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Machine learning-aided landslide hazard assessment : probabilistic slope stability analysis and displacement forecasting
No full textHangrutschungen sind Naturgefahren, die weltweit schwerwiegende Auswirkungen auf die Bevölkerung sowie auf die bebaute Umwelt haben und effektive Prognosen erfordern, um das Risiko zu verringern. Die Komplexität von Hangrutschungen, die auf die Unsicherheiten der geologischen Randbedingungen und der Auslösemechanismen zurückzuführen ist, stellt eine große Herausforderung für genaue Vorhersagen dar. Das Ziel der vorliegenden Dissertation bestand in der Entwicklung von Prognosemodellen für das Versagen von Böschungen. Zu diesem Zweck wurden physikalisch basierte Modelle mit datengetriebenen Verfahren kombiniert, wobei Machine Learning (Maschinelles Lernen) als verbindende Methode in Betracht gezogen wurde. Ein probabilistischer Ansatz, auf der Grundlage von intelligenten Ersatzmodellen, wurde entwickelt, um Zuverlässigkeitsanalysen der Böschungsstabilität unter Berücksichtigung der Unsicherheiten der Bodenkenngrößen durchzuführen. Dies ermöglichte eine effiziente und genaue Abschätzung der Versagenswahrscheinlichkeit von stauinduzierten Böschungen, die von einer schnellen Absenkung ausgelöst werden könnten. Die Anwendbarkeit dieses integrierten Ansatzes wurde anhand der Fallstudie des Huangtupo-Hangrutschung im Drei-Schluchten-Staudamm in China demonstriert. Darüber hinaus wurde Machine Learning eingesetzt, um die zeitliche Entwicklung von Hangbewegungen unter Zuhilfenahme von Überwachungsdaten vorherzusagen. Die Prognose von Hangbewegungen wurde als Ziel einer Zeitreihenanalyse betrachtet, wobei Langzeitmessungen von auslösenden Faktoren wie Niederschlag und Wasserstand des Stausees verwendet wurden. Machine Learning basierte Ersatzmodelle lieferten genaue Vorhersagen der Standsicherheit sowie der Hangbewegungen und können somit als wertvolle und effiziente Werkzeuge zur quantitativen Risikobewertung der Böschungsstabilität herangezogen werden.Landslides are natural hazards that severely impact communities and the built environment globally, requiring effective forecasting to mitigate their risk. The complex nature of landslide events, due to the inherent uncertainties of geological conditions and triggering mechanisms, poses a great challenge to accurate predictions. This thesis aims to develop forecasting methods for slope stability by merging physics-based models with data-driven techniques and utilizing machine learning as a unifying approach. A probabilistic framework based on intelligent surrogate models is developed to conduct reliability analyses of slope stability, accounting for the inherent uncertainties in soil parameters. This framework enables an efficient and accurate estimation of the probability of failure of reservoir slopes subject to rapid drawdown. The applicability of this integrated approach is demonstrated through the case study of the Huangtupo landslide in the Three Gorges Reservoir in China. Machine learning is further applied to forecast the dynamic evolution of landslides using monitoring data. The prediction of ground displacement is framed as a time series forecasting problem, leveraging long-term measurements of triggering factors such as precipitation and reservoir water level. Machine learning models offer accurate predictions for slope stability and ground displacements, serving as valuable and efficient tools in quantitative landslide hazard assessment.submitted by Carlotta GuardianiDissertation BOKU University 2024Mit deutscher Zusammenfassun
Long-term electrical resistivity data analysis for landslide monitoring : the case study of Rosano
No full textLAUREA MAGISTRALENell’ambito del monitoraggio frane l’integrazione di più metodologie è necessaria per la comprensione dei meccanismi che governano i fenomeni di instabilità di versante. Nel contesto italiano, le precipitazioni rappresentano il principale fattore d’innesco o riattivazione insieme alla ricarica idrica sotterranea. Tra le tecniche di monitoraggio attualmente impiegate, i metodi geoelettrici vengono utilizzati per la caratterizzazione geometrica del sottosuolo grazie all’informazione di carattere spaziale che forniscono, ottenendo come risultato delle immagini tomografiche di resistività elettrica. L’andamento temporale di questo parametro può essere messo in relazione con le variazioni del contenuto d’acqua interstiziale: il cambiamento delle condizioni di saturazione è strettamente legato all’evoluzione dei fenomeni franosi a dinamica lenta. Attraverso l’analisi time-lapse delle immagini tomografiche, il metodo di resistività elettrica si pone come un valido strumento di indagine dei processi idrogeologici che contribuiscono all’innesco dei movimenti franosi.
Il presente lavoro di tesi svolto presso il Geological Survey of Austria, con riferimento al caso studio di un’area in frana in Piemonte monitorata per circa tre anni, si inserisce all’interno di un progetto più ampio che si pone come obiettivo lo sviluppo di una rete di monitoraggio geoelettrico testata su diverse tipologie di frana.
Una fase di filtraggio dei dati ha preceduto il processamento delle serie storiche di resistività, effettuate con un software di inversione tomografica 2D e successivamente con un algoritmo che produce un modello di resistività elettrica definito sia nello spazio che nel tempo. L’interpretazione delle variazioni di resistività elettrica è stata svolta confrontando le misure geoelettriche con i dati acquisiti con metodi di monitoraggio tradizionale (misure inclinometriche, sensori di umidità, sensori piezometrici ecc.). I risultati di questo studio hanno dimostrato che la risposta elettrica del sottosuolo, durante gli eventi di precipitazione intensa, è rappresentativa dei processi di infiltrazione, con significative riduzioni di resistività causate dalla saturazione degli strati più superficiali.In the context of landslide monitoring, an integrated approach of several techniques is necessary to understand the mechanisms that control slope instability. In the Italian context, intense or prolonged precipitation is the main triggering factor for landslide activation/reactivation, together with groundwater table oscillations. Among the traditional monitoring techniques, the geoelectrical methods are currently employed for the investigation of the landslide body by means of high spatial resolution tomographic imaging. Temporal variations of the electrical resistivity can be correlated to changes in soil water content: modifications of slope saturation conditions are one of the most common precursors in the lead up to landslide activation. The analysis of time-lapse tomographic images is a powerful tool to investigate hydrogeological precursors of slope instability.
This thesis analyses and presents the results of three years of monitoring data from a composite landslide in Piedmont Region (Italy) collected with a geoelectrical permanent monitoring system. This work is involved in a larger project carried out at the Geological Survey of Austria, which aims to test this geophysical method in the frame of several case studies that are part of a geoelectrical monitoring network.
Data filtering preceded the inversion processing, which has been carried out with two different approaches: 2D tomographic inversion for independent time-step processing and a 4D algorithm producing a time-space model of the electrical resistivity. The interpretation of resistivity variations in the subsurface is based on the comparison with measurements from traditional monitoring techniques (inclinometric measurements, moisture and piezometric sensors etc.). The results of this study demonstrated that the electrical response of the slope during intense rainfall events is informative of the soil water content modifications induced by infiltration processes, with a significant decrease occurring within the shallow layers due to the saturation of the slope
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
- …
