TY - GEN A1 - Kovacs, Robert A1 - Ion, Alexandra A1 - Lopes, Pedro A1 - Oesterreich, Tim A1 - Filter, Johannes A1 - Otto, Philip A1 - Arndt, Tobias A1 - Ring, Nico A1 - Witte, Melvin A1 - Synytsia, Anton A1 - Baudisch, Patrick T1 - TrussFormer BT - 3D Printing Large Kinetic Structures T2 - The 31st Annual ACM Symposium on User Interface Software and Technology N2 - We present TrussFormer, an integrated end-to-end system that allows users to 3D print large-scale kinetic structures, i.e., structures that involve motion and deal with dynamic forces. TrussFormer builds on TrussFab, from which it inherits the ability to create static large-scale truss structures from 3D printed connectors and PET bottles. TrussFormer adds movement to these structures by placing linear actuators into them: either manually, wrapped in reusable components called assets, or by demonstrating the intended movement. TrussFormer verifies that the resulting structure is mechanically sound and will withstand the dynamic forces resulting from the motion. To fabricate the design, TrussFormer generates the underlying hinge system that can be printed on standard desktop 3D printers. We demonstrate TrussFormer with several example objects, including a 6-legged walking robot and a 4m-tall animatronics dinosaur with 5 degrees of freedom. KW - fabrication KW - 3D printing KW - variable geometry truss KW - large-scale mechanism Y1 - 2019 SN - 978-1-4503-5971-9 U6 - https://doi.org/10.1145/3290607.3311766 PB - Association for Computing Machinery CY - New York ER - TY - GEN A1 - Hernandez, Netzahualcoyotl A1 - Demiray, Burcu A1 - Arnrich, Bert A1 - Favela, Jesus T1 - An Exploratory Study to Detect Temporal Orientation Using Bluetooth's sensor T2 - PervasiveHealth'19: Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare N2 - Mobile sensing technology allows us to investigate human behaviour on a daily basis. In the study, we examined temporal orientation, which refers to the capacity of thinking or talking about personal events in the past and future. We utilise the mksense platform that allows us to use the experience-sampling method. Individual's thoughts and their relationship with smartphone's Bluetooth data is analysed to understand in which contexts people are influenced by social environments, such as the people they spend the most time with. As an exploratory study, we analyse social condition influence through a collection of Bluetooth data and survey information from participant's smartphones. Preliminary results show that people are likely to focus on past events when interacting with close-related people, and focus on future planning when interacting with strangers. Similarly, people experience present temporal orientation when accompanied by known people. We believe that these findings are linked to emotions since, in its most basic state, emotion is a state of physiological arousal combined with an appropriated cognition. In this contribution, we envision a smartphone application for automatically inferring human emotions based on user's temporal orientation by using Bluetooth sensors, we briefly elaborate on the influential factor of temporal orientation episodes and conclude with a discussion and lessons learned. KW - Mobile sensing KW - Temporal orientation KW - Social environment KW - Human behaviour KW - Bluetooth Y1 - 2019 SN - 978-1-4503-6126-2 U6 - https://doi.org/10.1145/3329189.3329223 SN - 2153-1633 SP - 292 EP - 297 PB - Association for Computing Machinery CY - New York ER - TY - GEN A1 - Fichte, Johannes Klaus A1 - Hecher, Markus A1 - Meier, Arne T1 - Counting Complexity for Reasoning in Abstract Argumentation T2 - The Thirty-Third AAAI Conference on Artificial Intelligence, the Thirty-First Innovative Applications of Artificial Intelligence Conference, the Ninth AAAI Symposium on Educational Advances in Artificial Intelligence N2 - In this paper, we consider counting and projected model counting of extensions in abstract argumentation for various semantics. When asking for projected counts we are interested in counting the number of extensions of a given argumentation framework while multiple extensions that are identical when restricted to the projected arguments count as only one projected extension. We establish classical complexity results and parameterized complexity results when the problems are parameterized by treewidth of the undirected argumentation graph. To obtain upper bounds for counting projected extensions, we introduce novel algorithms that exploit small treewidth of the undirected argumentation graph of the input instance by dynamic programming (DP). Our algorithms run in time double or triple exponential in the treewidth depending on the considered semantics. Finally, we take the exponential time hypothesis (ETH) into account and establish lower bounds of bounded treewidth algorithms for counting extensions and projected extension. Y1 - 2019 SN - 978-1-57735-809-1 SP - 2827 EP - 2834 PB - AAAI Press CY - Palo Alto ER - TY - GEN A1 - Perscheid, Cindy A1 - Uflacker, Matthias T1 - Integrating Biological Context into the Analysis of Gene Expression Data T2 - Distributed Computing and Artificial Intelligence, Special Sessions, 15th International Conference N2 - High-throughput RNA sequencing produces large gene expression datasets whose analysis leads to a better understanding of diseases like cancer. The nature of RNA-Seq data poses challenges to its analysis in terms of its high dimensionality, noise, and complexity of the underlying biological processes. Researchers apply traditional machine learning approaches, e. g. hierarchical clustering, to analyze this data. Until it comes to validation of the results, the analysis is based on the provided data only and completely misses the biological context. However, gene expression data follows particular patterns - the underlying biological processes. In our research, we aim to integrate the available biological knowledge earlier in the analysis process. We want to adapt state-of-the-art data mining algorithms to consider the biological context in their computations and deliver meaningful results for researchers. KW - Gene expression KW - Machine learning KW - Feature selection KW - Association rule mining KW - Biclustering KW - Knowledge bases Y1 - 2019 SN - 978-3-319-99608-0 SN - 978-3-319-99607-3 U6 - https://doi.org/10.1007/978-3-319-99608-0_41 SN - 2194-5357 SN - 2194-5365 VL - 801 SP - 339 EP - 343 PB - Springer CY - Cham ER - TY - GEN A1 - Lewis, Alison A1 - Glajar, Valentina A1 - Petrescu, Corina L. T1 - Introduction T2 - Cold War Spy Stories from Eastern Europe Y1 - 2019 SN - 978-1-64012-200-0 SN - 978-1-64012-187-4 SP - 1 EP - 26 PB - University of Nebraska Press CY - Lincoln ER - TY - GEN A1 - Hesse, Günter A1 - Matthies, Christoph A1 - Sinzig, Werner A1 - Uflacker, Matthias T1 - Adding Value by Combining Business and Sensor Data BT - an Industry 4.0 Use Case T2 - Database Systems for Advanced Applications N2 - Industry 4.0 and the Internet of Things are recent developments that have lead to the creation of new kinds of manufacturing data. Linking this new kind of sensor data to traditional business information is crucial for enterprises to take advantage of the data’s full potential. In this paper, we present a demo which allows experiencing this data integration, both vertically between technical and business contexts and horizontally along the value chain. The tool simulates a manufacturing company, continuously producing both business and sensor data, and supports issuing ad-hoc queries that answer specific questions related to the business. In order to adapt to different environments, users can configure sensor characteristics to their needs. KW - Industry 4.0 KW - Internet of Things KW - Data integration Y1 - 2019 SN - 978-3-030-18590-9 SN - 978-3-030-18589-3 U6 - https://doi.org/10.1007/978-3-030-18590-9_80 SN - 0302-9743 SN - 1611-3349 VL - 11448 SP - 528 EP - 532 PB - Springer CY - Cham ER - TY - GEN A1 - Turner, Bryan S. A1 - Contreras-Vejar, Yuri T1 - Introduction BT - Reflections on regimes of happiness T2 - Regimes of happiness : comparative and historical studies N2 - This book started as a conversation about successful societies and human development. It was originally based on a simple idea— it would be unusual if, in a society that might be reasonably deemed as successful, its citizens were deeply unhappy. This combination— successful societies and happy citizens— raised immediate and obvious problems. How might one define “success” when dealing, for example, with a society as large and as complex as the United States? We ran into equally major problems when trying to understand “happiness.” Yet one constantly hears political analysts talking about the success or failure of various democratic institutions. In ordinary conversations one constantly hears people talking about being happy or unhappy. In the everyday world, conversations about living in a successful society or about being happy do not appear to cause bewilderment or confusion. “Ordinary people” do not appear to find questions like— is your school successful or are you happily married?— meaningless or absurd. Yet, in the social sciences, both “successful societies” and “happy lives” are seen to be troublesome. As our research into happiness and success unfolded, the conundrums we discussed were threefold: societal conditions, measurements and concepts. What are the key social factors that are indispensable for the social and political stability of any given society? Is it possible to develop precise measures of social success that would give us reliable data? There are a range of economic indicators that might be associated with success, such as labor productivity, economic growth rates, low inflation and a robust GDP. Are there equally reliable political and social measures of a successful society and human happiness? For example, rule of law and the absence of large- scale corruption might be relevant to the assessment of societal happiness. These questions about success led us inexorably to what seems to be a futile notion: happiness. Economic variables such as income or psychological measures of well- being in terms of mental health could be easily analyzed; however, happiness is a dimension that has been elusive to the social sciences. In our unfolding conversation, there was also another stream of thought, namely that the social sciences appeared to be more open to the study of human unhappiness rather than happiness. Y1 - 2019 SN - 978-1-78308-886-7 SN - 978-1-78308-885-0 SP - 1 EP - 8 PB - Anthem Press CY - London ER - TY - GEN A1 - Stich, Michael A1 - Beta, Carsten T1 - Time-Delay Feedback Control of an Oscillatory Medium T2 - Biological Systems: Nonlinear Dynamics Approach N2 - The supercritical Hopf bifurcation is one of the simplest ways in which a stationary state of a nonlinear system can undergo a transition to stable self-sustained oscillations. At the bifurcation point, a small-amplitude limit cycle is born, which already at onset displays a finite frequency. If we consider a reaction-diffusion system that undergoes a supercritical Hopf bifurcation, its dynamics is described by the complex Ginzburg-Landau equation (CGLE). Here, we study such a system in the parameter regime where the CGLE shows spatio-temporal chaos. We review a type of time-delay feedback methods which is suitable to suppress chaos and replace it by other spatio-temporal solutions such as uniform oscillations, plane waves, standing waves, and the stationary state. Y1 - 2019 SN - 978-3-030-16585-7 SN - 978-3-030-16584-0 U6 - https://doi.org/10.1007/978-3-030-16585-7_1 SN - 2199-3041 SN - 2199-305X VL - 20 SP - 1 EP - 17 PB - Springer CY - Cham ER - TY - GEN A1 - Gonzalez-Lopez, Fernanda A1 - Pufahl, Luise T1 - A Landscape for Case Models T2 - Enterprise, Business-Process and Information Systems Modeling N2 - Case Management is a paradigm to support knowledge-intensive processes. The different approaches developed for modeling these types of processes tend to result in scattered models due to the low abstraction level at which the inherently complex processes are therein represented. Thus, readability and understandability is more challenging than that of traditional process models. By reviewing existing proposals in the field of process overviews and case models, this paper extends a case modeling language - the fragment-based Case Management (fCM) language - with the goal of modeling knowledge-intensive processes from a higher abstraction level - to generate a so-called fCM landscape. This proposal is empirically evaluated via an online experiment. Results indicate that interpreting an fCM landscape might be more effective and efficient than interpreting an informationally equivalent case model. KW - Case Management KW - Process landscape KW - Process map KW - Process architecture KW - Process model Y1 - 2019 SN - 978-3-030-20618-5 SN - 978-3-030-20617-8 U6 - https://doi.org/10.1007/978-3-030-20618-5_6 SN - 1865-1348 VL - 352 SP - 87 EP - 102 PB - Springer CY - Berlin ER - TY - GEN A1 - Bartz, Christian A1 - Yang, Haojin A1 - Bethge, Joseph A1 - Meinel, Christoph T1 - LoANs BT - Weakly Supervised Object Detection with Localizer Assessor Networks T2 - Computer Vision – ACCV 2018 Workshops N2 - Recently, deep neural networks have achieved remarkable performance on the task of object detection and recognition. The reason for this success is mainly grounded in the availability of large scale, fully annotated datasets, but the creation of such a dataset is a complicated and costly task. In this paper, we propose a novel method for weakly supervised object detection that simplifies the process of gathering data for training an object detector. We train an ensemble of two models that work together in a student-teacher fashion. Our student (localizer) is a model that learns to localize an object, the teacher (assessor) assesses the quality of the localization and provides feedback to the student. The student uses this feedback to learn how to localize objects and is thus entirely supervised by the teacher, as we are using no labels for training the localizer. In our experiments, we show that our model is very robust to noise and reaches competitive performance compared to a state-of-the-art fully supervised approach. We also show the simplicity of creating a new dataset, based on a few videos (e.g. downloaded from YouTube) and artificially generated data. Y1 - 2019 SN - 978-3-030-21074-8 SN - 978-3-030-21073-1 U6 - https://doi.org/10.1007/978-3-030-21074-8_29 SN - 0302-9743 SN - 1611-3349 VL - 11367 SP - 341 EP - 356 PB - Springer CY - Cham ER -