TY - GEN A1 - Rounsevell, Mark D. A. A1 - Metzger, Marc J. A1 - Walz, Ariane T1 - Operationalising ecosystem services in Europe T2 - Regional environmental change Y1 - 2019 U6 - https://doi.org/10.1007/s10113-019-01560-1 SN - 1436-3798 SN - 1436-378X VL - 19 IS - 8 SP - 2143 EP - 2149 PB - Springer CY - Heidelberg ER - TY - GEN A1 - Roumen, Thijs A1 - Shigeyama, Jotaro A1 - Rudolph, Julius Cosmo Romeo A1 - Grzelka, Felix A1 - Baudisch, Patrick T1 - SpringFit BT - Joints and mounts that fabricate on any laser cutter T2 - User Interface Software and Technology N2 - Joints are crucial to laser cutting as they allow making three-dimensional objects; mounts are crucial because they allow embedding technical components, such as motors. Unfortunately, mounts and joints tend to fail when trying to fabricate a model on a different laser cutter or from a different material. The reason for this lies in the way mounts and joints hold objects in place, which is by forcing them into slightly smaller openings. Such "press fit" mechanisms unfortunately are susceptible to the small changes in diameter that occur when switching to a machine that removes more or less material ("kerf"), as well as to changes in stiffness, as they occur when switching to a different material. We present a software tool called springFit that resolves this problem by replacing the problematic press fit-based mounts and joints with what we call cantilever-based mounts and joints. A cantilever spring is simply a long thin piece of material that pushes against the object to be held. Unlike press fits, cantilever springs are robust against variations in kerf and material; they can even handle very high variations, simply by using longer springs. SpringFit converts models in the form of 2D cutting plans by replacing all contained mounts, notch joints, finger joints, and t-joints. In our technical evaluation, we used springFit to convert 14 models downloaded from the web. KW - Laser cutting KW - fabrication KW - portability KW - reuse Y1 - 2019 SN - 978-1-4503-6816-2 U6 - https://doi.org/10.1145/3332165.3347930 SP - 727 EP - 738 PB - Association for Computing Machinery CY - New York ER - TY - GEN A1 - Rodriguez-Sillke, Yasmina A1 - Steinhoff, U. A1 - Bojarski, Christian A1 - Lissner, Donata A1 - Schumann, Michael A1 - Branchi, F. A1 - Siegmund, Britta A1 - Glauben, Rainer T1 - Deep immune profiling of human Peyer´s Patches in patients of inflammatory bowel diseases T2 - European journal of immunology Y1 - 2019 U6 - https://doi.org/10.1002/eji.201970300 SN - 0014-2980 SN - 1521-4141 VL - 49 SP - 203 EP - 204 PB - Wiley CY - Weinheim ER - TY - GEN A1 - Richly, Keven T1 - A survey on trajectory data management for hybrid transactional and analytical workloads T2 - IEEE International Conference on Big Data (Big Data) N2 - Rapid advances in location-acquisition technologies have led to large amounts of trajectory data. This data is the foundation for a broad spectrum of services driven and improved by trajectory data mining. However, for hybrid transactional and analytical workloads, the storing and processing of rapidly accumulated trajectory data is a non-trivial task. In this paper, we present a detailed survey about state-of-the-art trajectory data management systems. To determine the relevant aspects and requirements for such systems, we developed a trajectory data mining framework, which summarizes the different steps in the trajectory data mining process. Based on the derived requirements, we analyze different concepts to store, compress, index, and process spatio-temporal data. There are various trajectory management systems, which are optimized for scalability, data footprint reduction, elasticity, or query performance. To get a comprehensive overview, we describe and compare different exciting systems. Additionally, the observed similarities in the general structure of different systems are consolidated in a general blueprint of trajectory management systems. KW - Trajectory Data Management KW - Spatio-Temporal Data KW - Survey Y1 - 2019 SN - 978-1-5386-5035-6 U6 - https://doi.org/10.1109/BigData.2018.8622394 SN - 2639-1589 SP - 562 EP - 569 PB - IEEE CY - New York ER - TY - GEN A1 - Richly, Keven T1 - Leveraging spatio-temporal soccer data to define a graphical query language for game recordings T2 - IEEE International Conference on Big Data (Big Data) N2 - For professional soccer clubs, performance and video analysis are an integral part of the preparation and post-processing of games. Coaches, scouts, and video analysts extract information about strengths and weaknesses of their team as well as opponents by manually analyzing video recordings of past games. Since video recordings are an unstructured data source, it is a complex and time-intensive task to find specific game situations and identify similar patterns. In this paper, we present a novel approach to detect patterns and situations (e.g., playmaking and ball passing of midfielders) based on trajectory data. The application uses the metaphor of a tactic board to offer a graphical query language. With this interactive tactic board, the user can model a game situation or mark a specific situation in the video recording for which all matching occurrences in various games are immediately displayed, and the user can directly jump to the corresponding game scene. Through the additional visualization of key performance indicators (e.g.,the physical load of the players), the user can get a better overall assessment of situations. With the capabilities to find specific game situations and complex patterns in video recordings, the interactive tactic board serves as a useful tool to improve the video analysis process of professional sports teams. KW - Spatio-temporal data analysis KW - soccer analytics KW - graphical query language Y1 - 2019 SN - 978-1-5386-5035-6 U6 - https://doi.org/10.1109/BigData.2018.8622159 SN - 2639-1589 SP - 3456 EP - 3463 PB - IEEE CY - New York ER - TY - GEN A1 - Renz, Jan A1 - Meinel, Christoph T1 - The "Bachelor Project" BT - Project Based Computer Science Education T2 - 2019 IEEE Global Engineering Education Conference (EDUCON) N2 - One of the challenges of educating the next generation of computer scientists is to teach them to become team players, that are able to communicate and interact not only with different IT systems, but also with coworkers and customers with a non-it background. The “bachelor project” is a project based on team work and a close collaboration with selected industry partners. The authors hosted some of the teams since spring term 2014/15. In the paper at hand we explain and discuss this concept and evaluate its success based on students' evaluation and reports. Furthermore, the technology-stack that has been used by the teams is evaluated to understand how self-organized students in IT-related projects work. We will show that and why the bachelor is the most successful educational format in the perception of the students and how this positive results can be improved by the mentors. KW - computer science education KW - project based learning KW - bachelor project Y1 - 2019 SN - 978-1-5386-9506-7 U6 - https://doi.org/10.1109/EDUCON.2019.8725140 SN - 2165-9567 SP - 580 EP - 587 PB - IEEE CY - New York ER - TY - GEN A1 - Rastogi, Abhishake T1 - Tikhonov regularization with oversmoothing penalty for linear statistical inverse learning problems T2 - AIP Conference Proceedings : third international Conference of mathematical sciences (ICMS 2019) N2 - In this paper, we consider the linear ill-posed inverse problem with noisy data in the statistical learning setting. The Tikhonov regularization scheme in Hilbert scales is considered in the reproducing kernel Hilbert space framework to reconstruct the estimator from the random noisy data. We discuss the rates of convergence for the regularized solution under the prior assumptions and link condition. For regression functions with smoothness given in terms of source conditions the error bound can explicitly be established. KW - Statistical inverse problem KW - Tikhonov regularization KW - Hilbert Scales KW - Reproducing kernel Hilbert space KW - Minimax convergence rates Y1 - 2019 SN - 978-0-7354-1930-8 U6 - https://doi.org/10.1063/1.5136221 SN - 0094-243X VL - 2183 PB - American Institute of Physics CY - Melville ER - TY - GEN A1 - Radchuk, Viktoriia A1 - Kramer-Schadt, Stephanie A1 - Grimm, Volker T1 - Transferability of mechanistic ecological models is about emergence T2 - Trends in ecology and evolution Y1 - 2019 U6 - https://doi.org/10.1016/j.tree.2019.01.010 SN - 0169-5347 SN - 1872-8383 VL - 34 IS - 6 SP - 487 EP - 488 PB - Elsevier CY - London ER - TY - GEN A1 - Pérez Chaparro, Camilo Germán Alberto A1 - Mayer, Frank A1 - Beckendorf, Claudia T1 - Cardiovascular drift response over two different constant-load exercises in healthy non-athletes BT - case study T2 - Medicine and science in sports and exercise : official journal of the American College of Sports Medicine N2 - Cardiovascular drift (CV-d) is a steady increase in heart rate (HR) over time while performing constant load moderate intensity exercise (CME) > 20 min. CV-d presents problems for the prescription of exercise intensity by means of HR, because the work rate (WR) during exercise must be adjusted to maintain target HR, thus disturbing the intended effect of the exercise intervention. It has been shown that the increase in HR during CME is due to changes in WR and not to CV-d. Y1 - 2019 U6 - https://doi.org/10.1249/01.mss.0000561495.15163.50 SN - 0195-9131 SN - 1530-0315 VL - 51 IS - 6 SP - 329 EP - 329 PB - Lippincott Williams & Wilkins CY - Philadelphia ER - TY - GEN A1 - Przybylla, Mareen T1 - Interactive objects in physical computing and their role in the learning process T2 - Constructivist foundations N2 - The target article discusses the question of how educational makerspaces can become places supportive of knowledge construction. This question is too often neglected by people who run makerspaces, as they mostly explain how to use different tools and focus on the creation of a product. In makerspaces, often pupils also engage in physical computing activities and thus in the creation of interactive artifacts containing embedded systems, such as smart shoes or wristbands, plant monitoring systems or drink mixing machines. This offers the opportunity to reflect on teaching physical computing in computer science education, where similarly often the creation of the product is so strongly focused upon that the reflection of the learning process is pushed into the background. Y1 - 2019 SN - 1782-348X VL - 14 IS - 3 SP - 264 EP - 266 PB - Vrije Univ. CY - Bussels ER -