Suchergebnisse

"Wie kann neuer und bestehender multimedialer Content, insbesondere im E-Learning, auf verschiedensten Plattformen und Medien effizient genutzt werden?" Michael Herzog entwickelt entlang dieser Frage einen Lösungsansatz, der Medienbrüche verhindern kann und mit dem die Datengenerierung und Datenhaltung erleichtert wird. Standardisierung, Spezialisierung und Automatisierung von multimedialen Informationen und Informationsdienstleistungen wird so möglich.

When a crisis is unfolding, people no longer wait for an official statement from government actors; rather they turn to the news media, they go to Twitter or Facebook, they log onto forums and blogs, etc., because they expect information and they can get it quickly from various sources. In such a dynamic information environment, if a government lacks a policy on how to use social media, particularly in crisis situations (meaning it does not act, or act appropriately), then it may face a loss of credibility and struggle with the management of a crisis. To get ahead of this curve, debating the risks and opportunities of using social media is a critical first step to building a sound social media policy and identifying certain engagement guidelines. This report examines four different issue areas to analyze how social media is used in the context of risk and crisis communication. These areas include: public safety and preparedness; emergency warnings, alerts and requests for assistance; recovery efforts; and, finally, monitoring and situational awareness. In the context of each of these areas, we highlight the key literature and real-life examples to explore the risks vs. opportunities in the utility of social media. These four areas capture the role of engagement and strategy in both the risk and crisis space.

AbstractAccording to physicalism, everything is physical or metaphysically connected to the physical. If physicalism were true, it seems that we should – in principle – be able to reduce the descriptions and explanations of special sciences to physical ones, for example, explaining biological regularities, via chemistry, by the laws of particle physics. The multiple realization of the property types of the special sciences is often seen to be an obstacle to such epistemic reductions. Here, we introduce another, new argument against epistemic reduction. Based on mathematical complexity, we show that, under certain conditions, there can be "complexity barriers" that make epistemic reduction – in principle – unachievable even if physicalism were true.

Abstract. Large uncertainty remains about the amount of precipitation falling in the Indus River basin, particularly in the more mountainous northern part. While rain gauge measurements are often considered as a reference, they provide information for specific, often sparse, locations (point observations) and are subject to underestimation, particularly in mountain areas. Satellite observations and reanalysis data can improve our knowledge but validating their results is often difficult. In this study, we offer a cross-validation of 20 gridded datasets based on rain gauge, satellite, and reanalysis data, including the most recent and less studied APHRODITE-2, MERRA2, and ERA5. This original approach to cross-validation alternatively uses each dataset as a reference and interprets the result according to their dependency on the reference. Most interestingly, we found that reanalyses represent the daily variability of precipitation as well as any observational datasets, particularly in winter. Therefore, we suggest that reanalyses offer better estimates than non-corrected rain-gauge-based datasets where underestimation is problematic. Specifically, ERA5 is the reanalysis that offers estimates of precipitation closest to observations, in terms of amounts, seasonality, and variability, from daily to multi-annual scale. By contrast, satellite observations bring limited improvement at the basin scale. For the rain-gauge-based datasets, APHRODITE has the finest temporal representation of the precipitation variability, yet it importantly underestimates the actual amount. GPCC products are the only datasets that include a correction factor of the rain gauge measurements, but this factor likely remains too small. These findings highlight the need for a systematic characterisation of the underestimation of rain gauge measurements. ; European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 648609)

Acknowledgments The authors thank Ruth Rosenholtz for her detailed comments on this manuscript and for sharing the code of the TTM. We thank both reviewers for their insightful comments. A.B. was supported by the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreements No. 785907 (Human Brain Project SGA2) and No. 945539 (Human Brain Project SGA3). O.H.C. was supported by the Swiss National Science Foundation (SNF) 320030_176153 "Basics of visual processing: from elements to figures." A.D. was supported by the Swiss National Science Foundation grants No. 176153 "Basics of visual processing: from elements to figures" and No. 191718 "Towards machines that see like us: human eye movements for robust deep recurrent neural networks." D.W. was supported by the National Institutes of Health grant R01 CA236793. ; Peer reviewed ; Publisher PDF