Preservation of Cultural Heritage and Resources Threatened by Climate Change

With its wide spectrum of data, case studies, monitoring, and experimental and numerical simulation techniques, the multidisciplinary approach of material, environmental, and computer science applied to the conservation of cultural heritage offers several opportunities for the heritage science and conservation community to map and monitor state-of-the-art knowledge on natural and human-induced climate change impacts on cultural heritage—mainly constituted by the built environment—in Europe and Latin America. Geosciences’ Special Issue titled “Preservation of Cultural Heritage and Resources Threatened by Climate Change” was launched to take stock of the existing but still fragmentary knowledge on this challenge, and to enable the community to respond to the implementation of the Paris agreement. These 10 papers exploit a broad range of data derived from preventive conservation monitoring conducted indoors in museums, churches, historical buildings, or outdoors in archeological sites and city centers. Case studies presented in the papers focus on a well-assorted sample of decay phenomena occurring on heritage materials (e.g., surface recession and biomass accumulation on limestone, depositions of pollutant on marble, salt weathering on inorganic building materials, and weathering processes on mortars in many local- to regional-scale study areas in the Scandinavian Peninsula, the United Kingdom, Belgium, France, Italy, Greece, and Panama). Besides monitoring, the methodological approaches showcased include, but are not limited to, original material characterization, decay product characterization, and climate and numerical modelling on material components for assessing environmental impact and climate change effects

Approximate information filtering in structured peer-to-peer networks

Today';s content providers are naturally distributed and produce large amounts of information every day, making peer-to-peer data management a promising approach offering scalability, adaptivity to dynamics, and failure resilience. In such systems, subscribing with a continuous query is of equal importance as one-time querying since it allows the user to cope with the high rate of information production and avoid the cognitive overload of repeated searches. In the information filtering setting users specify continuous queries, thus subscribing to newly appearing documents satisfying the query conditions. Contrary to existing approaches providing exact information filtering functionality, this doctoral thesis introduces the concept of approximate information filtering, where users subscribe to only a few selected sources most likely to satisfy their information demand. This way, efficiency and scalability are enhanced by trading a small reduction in recall for lower message traffic. This thesis contains the following contributions: (i) the first architecture to support approximate information filtering in structured peer-to-peer networks, (ii) novel strategies to select the most appropriate publishers by taking into account correlations among keywords, (iii) a prototype implementation for approximate information retrieval and filtering, and (iv) a digital library use case to demonstrate the integration of retrieval and filtering in a unified system.Heutige Content-Anbieter sind verteilt und produzieren riesige Mengen an Daten jeden Tag. Daher wird die Datenhaltung in Peer-to-Peer Netzen zu einem vielversprechenden Ansatz, der Skalierbarkeit, Anpassbarkeit an Dynamik und Ausfallsicherheit bietet. Für solche Systeme besitzt das Abonnieren mit Daueranfragen die gleiche Wichtigkeit wie einmalige Anfragen, da dies dem Nutzer erlaubt, mit der hohen Datenrate umzugehen und gleichzeitig die Überlastung durch erneutes Suchen verhindert. Im Information Filtering Szenario legen Nutzer Daueranfragen fest und abonnieren dadurch neue Dokumente, die die Anfrage erfüllen. Im Gegensatz zu vorhandenen Ansätzen für exaktes Information Filtering führt diese Doktorarbeit das Konzept von approximativem Information Filtering ein. Ein Nutzer abonniert nur wenige ausgewählte Quellen, die am ehesten die Anfrage erfüllen werden. Effizienz und Skalierbarkeit werden verbessert, indem Recall gegen einen geringeren Nachrichtenverkehr eingetauscht wird. Diese Arbeit beinhaltet folgende Beiträge: (i) die erste Architektur für approximatives Information Filtering in strukturierten Peer-to-Peer Netzen, (ii) Strategien zur Wahl der besten Anbieter unter Berücksichtigung von Schlüsselwörter-Korrelationen, (iii) ein Prototyp, der approximatives Information Retrieval und Filtering realisiert und (iv) ein Anwendungsfall für Digitale Bibliotheken, der beide Funktionalitäten in einem vereinten System aufzeigt

Frozen Ground - The News Bulletin of the International Permafrost Association, No.25

Frozen Ground - The News Bulletin of the International Permafrost Association, No.2