Proceedings of the 2020 OMI Seminars (PROMIS 2020)

dc.contributor.editorDomaschka, Jörg
dc.date.accessioned2021-08-05T12:59:46Z
dc.date.available2021-08-05T12:59:46Z
dc.date.issued2021-08-05de
dc.description.abstractOMI is the acronym of the German name for the Institute of Information Resource Management located at Ulm University, Germany. Residing at the border between electrical engineering and computer science, we offer lectures spanning topics such as Computer Networks, Cloud Computing, and Parallel Computing. Our labs range from hands-on work using micro-controllers to programming challenges in operating system, High Performance Computing and Software-defined systems. We offer three seminars for our students: Selected Topics in Data Center Automation directed at Bachelor students from the computer science domain, Research Trends in Data Center Automation directed at Master students from the computer science domain, and Research Trends in the Internet of Things directed at Master students from the engineering majors. The seminars addresses topics interesting for system architects, reliability engineers, and DevOps engineers, but also data scientists mainly targeting automation, application and data management, as well as system modelling. Seminars proceed as follows: At the beginning of the course each student picks a topic and works on it. The tasks include researching the topic from a scientific angle (using scientific digital libraries), filtering and structuring content, and compiling a paper from it. Finally, the results of the work are presented in a talk. While the work is self-responsible, each student is assisted by an advisor who is an expert in the respective domain. The best papers of each year are selected to be published in this proceedings. Students may reject the publication of their work. In 2020 all three seminars took place twice, once in summer term (April - July) and once in winter term (November 2020 -February 2021). Due to the Covid pandemic they were organized as purely virtual events. Overall, 50 students participated in the courses, out of which 34 (68%) completed the course. Further, 16 (32%) were invited to publish their work in this proceedings and 12 accepted the invitation. The 2020 proceedings are structured in four parts: application management, system modelling, Internet of Things (IoT), and Machine Learning.de
dc.description.versionupdatedVersionde
dc.identifier.doihttp://dx.doi.org/10.18725/OPARU-38460
dc.identifier.issn2748-0003de
dc.identifier.urlhttps://oparu.uni-ulm.de/xmlui/123456789/38536
dc.identifier.urnhttp://nbn-resolving.de/urn:nbn:de:bsz:289-oparu-38536-9
dc.language.isoende
dc.publisherUniversität Ulm
dc.relation.haspartBaur, Andreas (2021): Packaging of kubernetes applications. http://dx.doi.org/10.18725/OPARU-38549
dc.relation.haspartRothmund, Kilian (2021): Immutable Linux distributionen mit LinuxKit. http://dx.doi.org/10.18725/OPARU-38583
dc.relation.haspartHerman, Artur (2021): Distributed shared memory frameworks: Comparison of implementations. http://dx.doi.org/10.18725/OPARU-38584
dc.relation.haspartScheible, Jens (2021): LoRa and LoRaWAN - An evaluation of scalability and reliability. http://dx.doi.org/10.18725/OPARU-38585
dc.relation.haspartHuynh, Misam (2021): Finding noisy neighbours and quantifying performance impact. http://dx.doi.org/10.18725/OPARU-38586
dc.relation.haspartEvangelista, Cristina (2021): Performance modelling of NoSQL DBMS. http://dx.doi.org/10.18725/OPARU-38587
dc.relation.haspartMüller, Kilian (2021): An assessment of the benefit of Covid-19 movement datasets for edge computing. http://dx.doi.org/10.18725/OPARU-38588
dc.relation.haspartEdlhuber, Jonas (2021): IoT and 5G communication. http://dx.doi.org/10.18725/OPARU-38589
dc.relation.haspartKammerer, Annalena (2021): Information-centric networks in the IoT. http://dx.doi.org/10.18725/OPARU-38590
dc.relation.haspartUlrich, Julian (2021): IoT live updating. http://dx.doi.org/10.18725/OPARU-38591
dc.relation.haspartSchauz, Philipp (2021): Sensor modalities connections in smart environments. http://dx.doi.org/10.18725/OPARU-38592
dc.relation.haspartLochner, Arne (2021): Modifications for synthetic data generation using generative adversarial networks. http://dx.doi.org/10.18725/OPARU-38593
dc.relation.haspartKirikkayis, Yusuf (2021): The autoML jungle - An overview. http://dx.doi.org/10.18725/OPARU-38594
dc.relation.haspartSchiessle, Pascal (2021): Datalog - An overview and outlook on a decade-old technology. http://dx.doi.org/10.18725/OPARU-38595
dc.rightsCC BY 4.0 Internationalde
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectSystem Modellingde
dc.subjectApplication Managementde
dc.subject.ddcDDC 004 / Data processing & computer sciencede
dc.subject.gndInternet der Dingede
dc.subject.gndMaschinelles Lernende
dc.subject.gndSystementwurfde
dc.subject.gndSoftwarelebenszyklusde
dc.subject.lcshInternet of thingsde
dc.subject.lcshMachine learningde
dc.subject.lcshSystem analysisde
dc.subject.lcshOperating systems (Computers)de
dc.subject.lcshApplication softwarede
dc.titleProceedings of the 2020 OMI Seminars (PROMIS 2020)de
dc.typeBuchde
uulm.affiliationGeneralFakultät für Ingenieurwissenschaften, Informatik und Psychologiede
uulm.affiliationSpecificInstitut für Organisation und Management von Informationssystemende
uulm.bibliographieuulm
uulm.categoryPublikationen
uulm.peerReviewjade
uulm.publisherPlaceUlm, Germanyde
uulm.seriesUlmEditorADomaschka, Jörgde
uulm.seriesUlmEditorBUniversität Ulm / Institut für Organisation und Management von Informationssystemende
uulm.seriesUlmNameToday I learnt: doing research - TIL:DRde
uulm.seriesUlmNumber1de
uulm.typeDCMITextde
uulm.updateStatusURNurn_new

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