Refine
Year of publication
Document Type
- Conference Proceeding (546) (remove)
Language
- English (391)
- German (153)
- Multiple languages (1)
- Russian (1)
Keywords
- Kommunikation (8)
- Produktion (8)
- Ausbildung (7)
- Gamification (7)
- Design (5)
- Eingebettetes System (5)
- Energieversorgung (5)
- Heart rhythm model (5)
- Modeling and simulation (5)
- Sensortechnik (5)
Institute
- Fakultät Elektrotechnik und Informationstechnik (E+I) (228)
- Fakultät Maschinenbau und Verfahrenstechnik (M+V) (131)
- Fakultät Medien und Informationswesen (M+I) (79)
- Fakultät Betriebswirtschaft und Wirtschaftsingenieurwesen (B+W) (67)
- Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (33)
- INES - Institut für Energiesystemtechnik (10)
- Zentrale Einrichtungen (6)
- IaF - Institut für angewandte Forschung (3)
- Forschung (1)
Über Chancen und Risiken von Computern an Schulen wird seit deren Einführung im Jahr 1984 kontrovers diskutiert. Neben Laptops und Tablets geht es heute um die Nutzung von Schulclouds und privaten Smartphones im Unterricht. Das Akronym dafür ist BYOD – »Bring Your Own Device«.
Dabei stellen sich grundsätzliche pädagogische und politische Fragen: Welcher Unterrichts- und Medienkonzepte bedarf es, um den Risiken der Digitalisierung vorzubeugen, die Schüler_innen aber zugleich an deren Chancen teilhaben zu lassen? Bei Netzanwendungen ist zudem der Datenschutz zu beachten, vor allem, wenn eigene Geräte genutzt werden sollen. So fördert das BMBF eine Schulcloud, in der Lehrkräfte und Schüler_innen wie bei Facebook Gruppen bilden, Dokumente austauschen und online darüber diskutieren können.
Das Buch greift die aktuelle Kontroverse auf und fragt nach den Zielen und Nebenwirkungen von »Bildung 4.0«. Was davon ist für die Unterrichtspraxis relevant? Und wessen Interessen werden bei welchen Konzepten vertreten?
Artificial Intelligence
(2019)
The TriRhenaTech alliance universities and their partners presented their competences in the field of artificial intelligence and their cross-border cooperations with the industry at the tri-national conference 'Artificial Intelligence : from Research to Application' on March 13th, 2019 in Offenburg. The TriRhenaTech alliance is a network of universities in the Upper Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe, and Offenburg, the Baden-Wuerttemberg Cooperative State University Loerrach, the French university network Alsace Tech (comprised of 14 'grandes écoles' in the fields of engineering, architecture and management) and the University of Applied Sciences and Arts Northwestern Switzerland. The alliance's common goal is to reinforce the transfer of knowledge, research, and technology, as well as the cross-border mobility of students.
With the surge in global data consumption with proliferation of Internet of Things (IoT), remote monitoring and control is increasingly becoming popular with a wide range of applications from emergency response in remote regions to monitoring of environmental parameters. Mesh networks are being employed to alleviate a number of issues associated with single-hop communication such as low area coverage, reliability, range and high energy consumption. Low-power Wireless Personal Area Networks (LoWPANs) are being used to help realize and permeate the applicability of IoT. In this paper, we present the design and test of IEEE 802.15.4-compliant smart IoT nodes with multi-hop routing. We first discuss the features of the software stack and design choices in hardware that resulted in high RF output power and then present field test results of different baseline network topologies in both rural and urban settings to demonstrate the deployability and scalability of our solution.
The excessive control signaling in Long Term Evolution networks required for dynamic scheduling impedes the deployment of ultra-reliable low latency applications. Semi-persistent scheduling was originally designed for constant bit-rate voice applications, however, very low control overhead makes it a potential latency reduction technique in Long Term Evolution. In this paper, we investigate resource scheduling in narrowband fourth generation Long Term Evolution networks through Network Simulator (NS3) simulations. The current release of NS3 does not include a semi-persistent scheduler for Long Term Evolution module. Therefore, we developed the semi-persistent scheduling feature in NS3 to evaluate and compare the performance in terms of uplink latency. We evaluate dynamic scheduling and semi-persistent scheduling in order to analyze the impact of resource scheduling methods on up-link latency.