Graph Representations for Higher-Order Logic and Theorem Proving

This paper presents the first use of graph neural networks (GNNs) for higher-order proof search and demonstrates that GNNs can improve upon state-of-the-art results in this domain. Interactive, higher-order theorem provers allow for the formalization of most mathematical theories and have been shown to pose a significant challenge for deep learning. Higher-order logic is highly expressive and, even though it is well-structured with a clearly defined grammar and semantics, there still remains no well-established method to convert formulas into graph-based representations. In this paper, we consider several graphical representations of higher-order logic and evaluate them against the HOList benchmark for higher-order theorem proving

Arctic sea ice thickness variability and change

Arctic sea ice thickness variability and change and their dependence on the atmospheric and oceanic forcing are at the core of research in Subtopic 2.1, Theme: Ongoing and Future Arctic and Antarctic Climate Change. Our research is particularly focused on a better process understanding and representation in models, and observations during MOSAiC play a strong role. The poster gives examples of such process studies focused on Arctic sea ice thickness variability and change. We outline observations of the long-term and regional variability and change of sea ice thickness using satellite remote sensing, airborne surveying, and ice mass balance buoys. Thermodynamic growth and its interaction with the atmosphere over leads and level ice serves as an example for our joint research interests. The poster also gives examples of causes of sea ice thinning, like increased ocean heat flux to the ice due to Atlantification, and consequences, e.g., for reduced sea ice volume transport through Fram Strait

Data-Driven Services in Manufacturing: Innovation, Engineering, Transformation, and Management

[No abstract available

An autonomous, multi-disciplinary sea ice - atmosphere - ocean observatory in the central Arctic

Although the polar oceans have been studied extensively during recent decades, year-round direct observations of sea ice, atmosphere and ocean are still relatively sparse. Hence, significant knowledge gaps exist in their complex interactions, and how they impact the evolution of the polar marine ecosystems. An important tool to fill these gaps has been developed and enhanced in recent years: autonomous, ice-based observation platforms. These buoys are capable of obtaining data on basin scales and year-round, including the largely undersampled winter periods. A key advantage over other observatory systems is that they send data in near-real time via satellite, contributing for example to numerical weather predictions through the Global Telecommunication Network (GTS). Here we present a concept for the implementation of a long-term strategy to monitor essential physical and biogeochemical parameters in the central Arctic Ocean year round and synchronously. We propose a combination of several new and innovative types of ice-based buoys, such as weather stations, ice mass balance buoys, ice-tethered bio-optical buoys and upper ocean profilers, with a scientific payload optimized to enable interdisciplinary research. Over the next 4 years, including the observational periods of the Year of Polar Prediction (YOPP, 2017-2019) and the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC, 2020), a network of these platforms will be (re-)deployed in the central Arctic Ocean each year, benefitting from international logistical efforts. The ultimate aim is to achieve a quasi-synoptic, basin-wide coverage of key parameters, such as air temperature, barometric pressure, wind speed and –direction, ice and snow thickness, incoming, reflected and transmitted irradiance, seawater temperature and salinity, chl-a and CDOM fluorescence, turbidity, oxygen and nitrate. Initial results from similar deployments since 2015 suggest that this approach has great potential to advance our understanding of many physical and biogeochemical processes and interactions in the polar oceans

A distributed atmosphere - sea ice - ocean observatory in the central Arctic

To understand the current evolution of the Arctic Ocean towards a less extensive, thinner and younger sea ice cover is one of the biggest challenges in climate research. Especially the lack of simultaneous in-situ observations of sea ice, ocean and atmospheric properties leads to significant knowledge gaps in their complex interactions, and how the associated processes impact the polar marine ecosystem. Here we present a concept for the implementation of a long-term strategy to monitor the most essential climate- and ecosystem parameters in the central Arctic Ocean, year round and synchronously. The basis of this strategy is the development and enhancement of a number of innovative autonomous observational platforms, such as rugged weather stations, ice mass balance buoys, ice-tethered bio-optical buoys and upper ocean profilers. The deployment of those complementing platforms in a distributed network enables the simultaneous collection of physical and biogeochemical in-situ data on basin scales and year round, including the largely undersampled winter periods. A key advantage over other observatory systems is that the data is sent via satellite in near-real time, contributing to numerical weather predictions through the Global Telecommunication Network (GTS) and to the International Arctic Buoy Programme (IABP). The first instruments were installed on ice floes in the Eurasian Basin in spring 2015 and 2016, yielding exceptional records of essential climate- and ecosystem-relevant parameters in one of the most inaccessible regions of this planet. Over the next 4 years, and including the observational periods of the Year of Polar Prediction (YOPP, 2017-2019) and the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC, 2020), the distributed observatory will be maintained by deployment of additional instruments in the central Arctic each year, benefitting from international logistical efforts

A distributed atmosphere - sea ice - ocean observatory in the central Arctic Ocean: concept and first results

To understand the current evolution of the Arctic Ocean towards a less extensive, thinner and younger sea ice cover is one of the biggest challenges in climate research. Especially the lack of simultaneous in-situ observations of sea ice, ocean and atmospheric properties leads to significant knowledge gaps in their complex interactions, and how the associated processes impact the polar marine ecosystem. Here we present a concept for the implementation of a long-term strategy to monitor the most essential climate- and ecosystem parameters in the central Arctic Ocean, year round and synchronously. The basis of this strategy is the development and enhancement of a number of innovative autonomous observational platforms, such as rugged weather stations, ice mass balance buoys, ice-tethered bio-optical buoys and upper ocean profilers. The deployment of those complementing platforms in a distributed network enables the simultaneous collection of physical and biogeochemical in-situ data on basin scales and year round, including the largely undersampled winter periods. A key advantage over other observatory systems is that the data is sent via satellite in near-real time, contributing to numerical weather predictions through the Global Telecommunication Network (GTS) and to the International Arctic Buoy Programme (IABP). The first instruments were installed on ice floes in the Eurasian Basin in spring 2015 and 2016, yielding exceptional records of essential climate- and ecosystem-relevant parameters in one of the most inaccessible regions of this planet. Over the next 4 years, and including the observational periods of the Year of Polar Prediction (YOPP, 2017-2019) and the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC, 2020), the distributed observatory will be continued and extended by deployments of additional instruments in the central Arctic each year, benefitting from international logistical efforts. The continuous data generated by this new autonomous drifting system is expected to provide new insights into the complex Arctic climate- and ecosystem on multiple scales. It is especially valuable in the context of the MOSAiC experiment, extending its coverage both in space and time

Low-Cost Image Generation for Immersive Multi-Screen Environments

Rabe F, Fröhlich C, Latoschik ME. Low-Cost Image Generation for Immersive Multi-Screen Environments. In: Latoschik ME, Fröhlich B, eds. Virtuelle und Erweiterte Realität – 4. Workshop der GI-Fachgruppe VR/AR. Aachen, Germany: Shaker; 2007: 65-76.This paper describes the configuration of a cost-efficient monolithic render server aimed at multi-screen Virtual Reality display devices. The system uses common Of-The-Shelf (OTS) PC components and feeds up to 6 independent screens via 3 graphics pipes with the potential to feed up to 12 screens. The internal graphics accelerators each use at least 8 PCIe lanes which results in sufficient bandwidth. Performance measurements are provided for several benchmarks which compare the system's performance to well established network based render clusters