TY - CHAP A1 - Kiy, Alexander A1 - Lucke, Ulrike A1 - Zoerner, Dietmar T1 - An adaptive personal learning environment architecture T2 - Architecture of Computing Systems – ARCS 2014 Lecture Notes in Computer Science N2 - Institutions are facing the challenge to integrate legacy systems with steadily growing new ones, using different technologies and interaction patterns. With the demand of offering the best potential of all systems, several not matching systems including their functions have to be aggregated and offered in a useable way. This paper presents an adaptive, generalizable and self-organized Personal Learning Environment (PLE) framework with the potential to integrate several heterogeneous services using a service-oriented architecture. First, a general overview over the field is given, followed by the description of the core components of the PLE framework. A prototypical implementation is presented. Finally, it’s shown how the PLE framework can be dynamically adapted to a changing system environment, reflecting experiences from first user studies. KW - Service-oriented architecture KW - Personal Learning Environment KW - University Service Bus Y1 - 2014 SN - 978-3-319-04890-1 VL - 2014 IS - 8350 SP - 60 EP - 71 PB - Springer ER - TY - CHAP A1 - Kiy, Alexander A1 - Grünwald, Franka A1 - Zoerner, Dietmar A1 - Lucke, Ulrike ED - Trasch, Stephan ED - Plötzner, Rolf ED - Schneider, Gerhard ED - Sassiat, Daniel ED - Gayer, Claudia ED - Wöhrle, Nicole T1 - Ein Hochschul-App-Framework: Hybrid und modular T2 - DeLFI 2014 - Die 12. e-Learning Fachtagung Informatik Lecture Notes in Informatics N2 - Mobile Endgeräte und die dazugehörigen Applikationen sind zu einem unverzichtbaren Bestandteil des täglichen Lebens geworden und ermöglichen den ortsund zeitunabhängigen Zugriff auf wichtige Informationen. Hochschulspezifische An- gebote sind im mobilen Bereich hingegen noch immer nicht flächendeckend anzutreffen und lassen sich i. d. R. nur auf Einzelaktivitäten Studierender und Lehrender zurückführen. Dabei können mobile Applikationen einen essentiellen Beitrag zur Verbesserung der studentischen Selbstorganisation sowie für die Ausgestaltung und Ergänzung von konkreten Lehr-/Lernszenarien leisten. Dieser Artikel stellt ein modulares Hochschul-App-Framework vor, das sowohl zentrale campusbezogene Dienste als auch dezentrale Lernapplikationen unter einer Oberfläche vereint anbietet. Anhand einer Analyse von Stärken und Schwächen werden verschiedene Ansätze in Hinblick auf Anforderungen, Entwicklung, Wartung und Betrieb der Hochschul-App zusammengefasst und bewertet. Es wird auf die zugrundeliegende serviceorientierte Architektur eingegangen, die eine Portierung der Applikation auf andere Hochschulen mit einem vertretbaren Aufwand ermöglicht. Der Beitrag schließt mit einer Darstellung der ersten Ergebnisse und weiterführender Überlegungen und Arbeiten. Y1 - 2014 UR - https://subs.emis.de/LNI/Proceedings/Proceedings233/article18.html SN - 978-3-88579-627-5 IS - P-233 SP - 205 EP - 216 PB - Gesellschaft für Informatik e.V. CY - Bonn ER - TY - JOUR A1 - Dornhege, Guido A1 - Blankertz, Benjamin A1 - Krauledat, Matthias A1 - Losch, Florian A1 - Curio, Gabriel A1 - Müller, Klaus-Robert T1 - Combined optimization of spatial and temporal filters for improving brain-computer interfacing JF - IEEE transactions on bio-medical electronics N2 - Brain-computer interface (BCI) systems create a novel communication channel from the brain to an output de ice by bypassing conventional motor output pathways of nerves and muscles. Therefore they could provide a new communication and control option for paralyzed patients. Modern BCI technology is essentially based on techniques for the classification of single-trial brain signals. Here we present a novel technique that allows the simultaneous optimization of a spatial and a spectral filter enhancing discriminability rates of multichannel EEG single-trials. The evaluation of 60 experiments involving 22 different subjects demonstrates the significant superiority of the proposed algorithm over to its classical counterpart: the median classification error rate was decreased by 11%. Apart from the enhanced classification, the spatial and/or the spectral filter that are determined by the algorithm can also be used for further analysis of the data, e.g., for source localization of the respective brain rhythms. KW - brain-computer interface KW - common spatial patterns KW - EEG KW - event-related desynchronization KW - single-trial-analysis Y1 - 2006 U6 - https://doi.org/10.1109/TBME.2006.883649 SN - 0018-9294 VL - 53 IS - 11 SP - 2274 EP - 2281 PB - IEEE CY - New York ER - TY - JOUR A1 - Bordihn, Henning A1 - Holzer, Markus T1 - Programmed grammars and their relation to the LBA problem JF - Acta informatica N2 - We consider generating and accepting programmed grammars with bounded degree of non-regulation, that is, the maximum number of elements in success or in failure fields of the underlying grammar. In particular, it is shown that this measure can be restricted to two without loss of descriptional capacity, regardless of whether arbitrary derivations or left-most derivations are considered. Moreover, in some cases, precise characterizations of the linear bounded automaton problem in terms of programmed grammars are obtained. Thus, the results presented in this paper shed new light on some longstanding open problem in the theory of computational complexity. KW - programmed grammars KW - accepting grammars KW - LBA problem KW - degree of non-regulation KW - leftmost derivations Y1 - 2006 U6 - https://doi.org/10.1007/s00236-006-0017-9 SN - 0001-5903 VL - 43 SP - 223 EP - 242 PB - Elsevier CY - New York ER - TY - JOUR A1 - Prasse, Paul A1 - Iversen, Pascal A1 - Lienhard, Matthias A1 - Thedinga, Kristina A1 - Bauer, Christopher A1 - Herwig, Ralf A1 - Scheffer, Tobias T1 - Matching anticancer compounds and tumor cell lines by neural networks with ranking loss JF - NAR: genomics and bioinformatics N2 - Computational drug sensitivity models have the potential to improve therapeutic outcomes by identifying targeted drug components that are likely to achieve the highest efficacy for a cancer cell line at hand at a therapeutic dose. State of the art drug sensitivity models use regression techniques to predict the inhibitory concentration of a drug for a tumor cell line. This regression objective is not directly aligned with either of these principal goals of drug sensitivity models: We argue that drug sensitivity modeling should be seen as a ranking problem with an optimization criterion that quantifies a drug's inhibitory capacity for the cancer cell line at hand relative to its toxicity for healthy cells. We derive an extension to the well-established drug sensitivity regression model PaccMann that employs a ranking loss and focuses on the ratio of inhibitory concentration and therapeutic dosage range. We find that the ranking extension significantly enhances the model's capability to identify the most effective anticancer drugs for unseen tumor cell profiles based in on in-vitro data. Y1 - 2022 U6 - https://doi.org/10.1093/nargab/lqab128 SN - 2631-9268 VL - 4 IS - 1 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Steinert, Fritjof A1 - Stabernack, Benno T1 - Architecture of a low latency H.264/AVC video codec for robust ML based image classification how region of interests can minimize the impact of coding artifacts JF - Journal of Signal Processing Systems for Signal, Image, and Video Technology N2 - The use of neural networks is considered as the state of the art in the field of image classification. A large number of different networks are available for this purpose, which, appropriately trained, permit a high level of classification accuracy. Typically, these networks are applied to uncompressed image data, since a corresponding training was also carried out using image data of similar high quality. However, if image data contains image errors, the classification accuracy deteriorates drastically. This applies in particular to coding artifacts which occur due to image and video compression. Typical application scenarios for video compression are narrowband transmission channels for which video coding is required but a subsequent classification is to be carried out on the receiver side. In this paper we present a special H.264/Advanced Video Codec (AVC) based video codec that allows certain regions of a picture to be coded with near constant picture quality in order to allow a reliable classification using neural networks, whereas the remaining image will be coded using constant bit rate. We have combined this feature with the ability to run with lowest latency properties, which is usually also required in remote control applications scenarios. The codec has been implemented as a fully hardwired High Definition video capable hardware architecture which is suitable for Field Programmable Gate Arrays. KW - H.264 KW - Advanced Video Codec (AVC) KW - Low Latency KW - Region of Interest KW - Machine Learning KW - Inference KW - FPGA KW - Hardware accelerator Y1 - 2022 U6 - https://doi.org/10.1007/s11265-021-01727-2 SN - 1939-8018 SN - 1939-8115 VL - 94 IS - 7 SP - 693 EP - 708 PB - Springer CY - New York ER - TY - JOUR A1 - Bauer, Chris A1 - Herwig, Ralf A1 - Lienhard, Matthias A1 - Prasse, Paul A1 - Scheffer, Tobias A1 - Schuchhardt, Johannes T1 - Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types JF - Journal of translational medicine N2 - Background: There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually. Methods: In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data. Results: We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: . Conclusions: Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the interactive knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs. KW - Literature mining KW - Anti-cancer drugs KW - Tumor types KW - Word embeddings KW - Database Y1 - 2021 U6 - https://doi.org/10.1186/s12967-021-02941-z SN - 1479-5876 VL - 19 IS - 1 PB - BioMed Central CY - London ER - TY - GEN A1 - Marwecki, Sebastian A1 - Baudisch, Patrick T1 - Scenograph BT - Fitting Real-Walking VR Experiences into Various Tracking Volumes T2 - UIST '18: Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology N2 - When developing a real-walking virtual reality experience, designers generally create virtual locations to fit a specific tracking volume. Unfortunately, this prevents the resulting experience from running on a smaller or differently shaped tracking volume. To address this, we present a software system called Scenograph. The core of Scenograph is a tracking volume-independent representation of real-walking experiences. Scenograph instantiates the experience to a tracking volume of given size and shape by splitting the locations into smaller ones while maintaining narrative structure. In our user study, participants' ratings of realism decreased significantly when existing techniques were used to map a 25m2 experience to 9m2 and an L-shaped 8m2 tracking volume. In contrast, ratings did not differ when Scenograph was used to instantiate the experience. KW - Virtual reality KW - real-walking KW - locomotion Y1 - 2018 SN - 978-1-4503-5948-1 U6 - https://doi.org/10.1145/3242587.3242648 SP - 511 EP - 520 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Bailis, Peter A1 - Dillahunt, Tawanna A1 - Müller, Stefanie A1 - Baudisch, Patrick T1 - Research for Practice: Technology for Underserved Communities; Personal Fabrication JF - Communications of the ACM / Association for Computing Machinery N2 - THIS INSTALLMENT OF Research for Practice provides curated reading guides to technology for underserved communities and to new developments in personal fabrication. First, Tawanna Dillahunt describes design considerations and technology for underserved and impoverished communities. Designing for the more than 1.6 billion impoverished individuals worldwide requires special consideration of community needs, constraints, and context. Her selections span protocols for poor-quality communication networks, community-driven content generation, and resource and public service discovery. Second, Stefanie Mueller and Patrick Baudisch provide an overview of recent advances in personal fabrication (for example, 3D printers). Y1 - 2017 U6 - https://doi.org/10.1145/3080188 SN - 0001-0782 SN - 1557-7317 VL - 60 SP - 46 EP - 49 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Huang, Yizhen A1 - Richter, Eric A1 - Kleickmann, Thilo A1 - Wiepke, Axel A1 - Richter, Dirk T1 - Classroom complexity affects student teachers’ behavior in a VR classroom JF - Computers & education : an international journal N2 - Student teachers often struggle to keep track of everything that is happening in the classroom, and particularly to notice and respond when students cause disruptions. The complexity of the classroom environment is a potential contributing factor that has not been empirically tested. In this experimental study, we utilized a virtual reality (VR) classroom to examine whether classroom complexity affects the likelihood of student teachers noticing disruptions and how they react after noticing. Classroom complexity was operationalized as the number of disruptions and the existence of overlapping disruptions (multidimensionality) as well as the existence of parallel teaching tasks (simultaneity). Results showed that student teachers (n = 50) were less likely to notice the scripted disruptions, and also less likely to respond to the disruptions in a comprehensive and effortful manner when facing greater complexity. These results may have implications for both teacher training and the design of VR for training or research purpose. This study contributes to the field from two aspects: 1) it revealed how features of the classroom environment can affect student teachers' noticing of and reaction to disruptions; and 2) it extends the functionality of the VR environment-from a teacher training tool to a testbed of fundamental classroom processes that are difficult to manipulate in real-life. KW - Augmented and virtual reality KW - Simulations KW - Improving classroom KW - teaching KW - Media in education KW - Pedagogical issues Y1 - 2021 U6 - https://doi.org/10.1016/j.compedu.2020.104100 SN - 0360-1315 SN - 1873-782X VL - 163 PB - Elsevier CY - Oxford ER -