TY - JOUR A1 - Meinel, Christoph A1 - Klotz, Volker T1 - The first 10 years of the ECCC digital library Y1 - 2006 UR - http://portal.acm.org/cacm U6 - https://doi.org/10.1145/1107458.1107484 ER - TY - JOUR A1 - Grünewald, Franka A1 - Meinel, Christoph T1 - Implementation and Evaluation of Digital E-Lecture Annotation in Learning Groups to Foster Active Learning JF - IEEE transactions on learning technologies N2 - The use of video lectures in distance learning involves the two major problems of searchability and active user participation. In this paper, we promote the implementation and usage of a collaborative educational video annotation functionality to overcome these two challenges. Different use cases and requirements, as well as details of the implementation, are explained. Furthermore, we suggest more improvements to foster a culture of participation and an algorithm for the extraction of semantic data. Finally, evaluations in the form of user tests and questionnaires in a MOOC setting are presented. The results of the evaluation are promising, as they indicate not only that students perceive it as useful, but also that the learning effectiveness increases. The combination of personal lecture video annotations with a semantic topic map was also evaluated positively and will thus be investigated further, as will the implementation in a MOOC context. KW - eLectures KW - tele-teaching KW - video annotation KW - collaborative learning Y1 - 2015 U6 - https://doi.org/10.1109/TLT.2015.2396042 SN - 1939-1382 VL - 8 IS - 3 SP - 286 EP - 298 PB - Inst. of Electr. and Electronics Engineers CY - Los Alamitos ER - TY - JOUR A1 - Meinel, Christoph A1 - Wang, Long T1 - Building content clusters based on modelling page pairs N2 - We give a new view on building content clusters from page pair models. We measure the heuristic importance within every two pages by computing the distance of their accessed positions in usage sessions. We also compare our page pair models with the classical pair models used in information theories and natural language processing, and give different evaluation methods to build the reasonable content communities. And we finally interpret the advantages and disadvantages of our models from detailed experiment results Y1 - 2006 UR - http://www.springerlink.com/content/105633/ U6 - https://doi.org/10.1007/11610113_85 ER - TY - JOUR A1 - Jobst, Birgit A1 - Köppen, Eva A1 - Lindberg, Tilmann A1 - Moritz, Josephine A1 - Rhinow, Holger A1 - Meinel, Christoph T1 - The faith-factor in design thinking : creative confidence through education at the design thinking schools Potsdam and Standford? Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Noweski, Christine A1 - Scheer, Andrea A1 - Büttner, Nadja A1 - Thienen, Julia von A1 - Erdmann, Johannes A1 - Meinel, Christoph T1 - Towards a paradigm shift in education practice : developing twenty-first century skills with design thinking Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Gumienny, Raja A1 - Gericke, Lutz A1 - Wenzel, Matthias A1 - Meinel, Christoph T1 - Tele-board in use : applying aq digital whiteboard system in different situations and setups Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Thienen, Julia von A1 - Noweski, Christine A1 - Rauth, Ingo A1 - Meinel, Christoph A1 - Lange, Sabine T1 - If you want to know who are, tell me where you are : the importance of places Y1 - 2012 ER - TY - JOUR A1 - Meinel, Christoph A1 - Leifer, Larry T1 - Design thinking research Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Meinel, Christoph A1 - Leifer, Larry T1 - Design thinking research Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Gumienny, Raja A1 - Meinel, Christoph A1 - Gericke, Lutz A1 - Quasthoff, Matthias A1 - LoBue, Peter A1 - Willems, Christian T1 - Tele-board : enabling efficient collaboration in digital design spaces across time and distance Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Thienen, Julia von A1 - Noweski, Christine A1 - Meinel, Christoph A1 - Rauth, Ingo T1 - The co-evolution of theory and practice in design thinking - or - "Mind the oddness trap!" Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Lindberg, Tilmann A1 - Köppen, Eva A1 - Rauth, Ingo A1 - Meinel, Christoph T1 - On the perection, adoption and Implementation of design thinking in the IT industry Y1 - 2012 ER - TY - JOUR A1 - Gericke, Lutz A1 - Gumienny, Raja A1 - Meinel, Christoph T1 - Tele-board : folow the traces of your design process history Y1 - 2012 ER - TY - JOUR A1 - Meinel, Christoph A1 - Leifer, Larry T1 - Design thinking research Y1 - 2012 ER - TY - JOUR A1 - Bröker, Kathrin ED - Schubert, Sigrid ED - Schwill, Andreas T1 - Unterstützung Informatik-Studierender durch ein Lernzentrum JF - HDI 2014 : Gestalten von Übergängen N2 - In diesem Papier wird das Konzept eines Lernzentrums für die Informatik (LZI) an der Universität Paderborn vorgestellt. Ausgehend von den fachspezifischen Schwierigkeiten der Informatik Studierenden werden die Angebote des LZIs erläutert, die sich über die vier Bereiche Individuelle Beratung und Betreuung, „Offener Lernraum“, Workshops und Lehrveranstaltungen sowie Forschung erstrecken. Eine erste Evaluation mittels Feedbackbögen zeigt, dass das Angebot bei den Studierenden positiv aufgenommen wird. Zukünftig soll das Angebot des LZIs weiter ausgebaut und verbessert werden. Ausgangsbasis dazu sind weitere Studien. Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-84754 VL - 2015 IS - 9 SP - 189 EP - 197 ER - TY - JOUR A1 - Middelanis, Robin A1 - Willner, Sven N. A1 - Otto, Christian A1 - Kuhla, Kilian A1 - Quante, Lennart A1 - Levermann, Anders T1 - Wave-like global economic ripple response to Hurricane Sandy JF - Environmental research letters : ERL / Institute of Physics N2 - Tropical cyclones range among the costliest disasters on Earth. Their economic repercussions along the supply and trade network also affect remote economies that are not directly affected. We here simulate possible global repercussions on consumption for the example case of Hurricane Sandy in the US (2012) using the shock-propagation model Acclimate. The modeled shock yields a global three-phase ripple: an initial production demand reduction and associated consumption price decrease, followed by a supply shortage with increasing prices, and finally a recovery phase. Regions with strong trade relations to the US experience strong magnitudes of the ripple. A dominating demand reduction or supply shortage leads to overall consumption gains or losses of a region, respectively. While finding these repercussions in historic data is challenging due to strong volatility of economic interactions, numerical models like ours can help to identify them by approaching the problem from an exploratory angle, isolating the effect of interest. For this, our model simulates the economic interactions of over 7000 regional economic sectors, interlinked through about 1.8 million trade relations. Under global warming, the wave-like structures of the economic response to major hurricanes like the one simulated here are likely to intensify and potentially overlap with other weather extremes. KW - supply chains KW - Hurricane Sandy KW - economic ripples KW - extreme weather KW - impacts KW - loss propagation KW - natural disasters Y1 - 2021 U6 - https://doi.org/10.1088/1748-9326/ac39c0 SN - 1748-9326 VL - 16 IS - 12 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Quante, Lennart A1 - Willner, Sven N. A1 - Middelanis, Robin A1 - Levermann, Anders T1 - Regions of intensification of extreme snowfall under future warming JF - Scientific reports N2 - Due to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century. Y1 - 2021 U6 - https://doi.org/10.1038/s41598-021-95979-4 SN - 2045-2322 VL - 11 IS - 1 PB - Macmillan Publishers Limited, part of Springer Nature CY - Berlin ER - TY - JOUR A1 - Schirrmann, Michael A1 - Landwehr, Niels A1 - Giebel, Antje A1 - Garz, Andreas A1 - Dammer, Karl-Heinz T1 - Early detection of stripe rust in winter wheat using deep residual neural networks JF - Frontiers in plant science : FPLS N2 - Stripe rust (Pst) is a major disease of wheat crops leading untreated to severe yield losses. The use of fungicides is often essential to control Pst when sudden outbreaks are imminent. Sensors capable of detecting Pst in wheat crops could optimize the use of fungicides and improve disease monitoring in high-throughput field phenotyping. Now, deep learning provides new tools for image recognition and may pave the way for new camera based sensors that can identify symptoms in early stages of a disease outbreak within the field. The aim of this study was to teach an image classifier to detect Pst symptoms in winter wheat canopies based on a deep residual neural network (ResNet). For this purpose, a large annotation database was created from images taken by a standard RGB camera that was mounted on a platform at a height of 2 m. Images were acquired while the platform was moved over a randomized field experiment with Pst-inoculated and Pst-free plots of winter wheat. The image classifier was trained with 224 x 224 px patches tiled from the original, unprocessed camera images. The image classifier was tested on different stages of the disease outbreak. At patch level the image classifier reached a total accuracy of 90%. To test the image classifier on image level, the image classifier was evaluated with a sliding window using a large striding length of 224 px allowing for fast test performance. At image level, the image classifier reached a total accuracy of 77%. Even in a stage with very low disease spreading (0.5%) at the very beginning of the Pst outbreak, a detection accuracy of 57% was obtained. Still in the initial phase of the Pst outbreak with 2 to 4% of Pst disease spreading, detection accuracy with 76% could be attained. With further optimizations, the image classifier could be implemented in embedded systems and deployed on drones, vehicles or scanning systems for fast mapping of Pst outbreaks. KW - yellow rust KW - monitoring KW - deep learning KW - wheat crops KW - image recognition KW - camera sensor KW - ResNet KW - smart farming Y1 - 2021 U6 - https://doi.org/10.3389/fpls.2021.469689 SN - 1664-462X VL - 12 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Thon, Ingo A1 - Landwehr, Niels A1 - De Raedt, Luc T1 - Stochastic relational processes efficient inference and applications JF - Machine learning N2 - One of the goals of artificial intelligence is to develop agents that learn and act in complex environments. Realistic environments typically feature a variable number of objects, relations amongst them, and non-deterministic transition behavior. While standard probabilistic sequence models provide efficient inference and learning techniques for sequential data, they typically cannot fully capture the relational complexity. On the other hand, statistical relational learning techniques are often too inefficient to cope with complex sequential data. In this paper, we introduce a simple model that occupies an intermediate position in this expressiveness/efficiency trade-off. It is based on CP-logic (Causal Probabilistic Logic), an expressive probabilistic logic for modeling causality. However, by specializing CP-logic to represent a probability distribution over sequences of relational state descriptions and employing a Markov assumption, inference and learning become more tractable and effective. Specifically, we show how to solve part of the inference and learning problems directly at the first-order level, while transforming the remaining part into the problem of computing all satisfying assignments for a Boolean formula in a binary decision diagram. We experimentally validate that the resulting technique is able to handle probabilistic relational domains with a substantial number of objects and relations. KW - Statistical relational learning KW - Stochastic relational process KW - Markov processes KW - Time series KW - CP-Logic Y1 - 2011 U6 - https://doi.org/10.1007/s10994-010-5213-8 SN - 0885-6125 VL - 82 IS - 2 SP - 239 EP - 272 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Cilia, Elisa A1 - Landwehr, Niels A1 - Passerini, Andrea T1 - Relational feature mining with hierarchical multitask kFOIL JF - Fundamenta informaticae N2 - We introduce hierarchical kFOIL as a simple extension of the multitask kFOIL learning algorithm. The algorithm first learns a core logic representation common to all tasks, and then refines it by specialization on a per-task basis. The approach can be easily generalized to a deeper hierarchy of tasks. A task clustering algorithm is also proposed in order to automatically generate the task hierarchy. The approach is validated on problems of drug-resistance mutation prediction and protein structural classification. Experimental results show the advantage of the hierarchical version over both single and multi task alternatives and its potential usefulness in providing explanatory features for the domain. Task clustering allows to further improve performance when a deeper hierarchy is considered. Y1 - 2011 U6 - https://doi.org/10.3233/FI-2011-604 SN - 0169-2968 VL - 113 IS - 2 SP - 151 EP - 177 PB - IOS Press CY - Amsterdam ER -