Efficient Machine-type Communication using Multi-metric Context-awareness for Cars used as Mobile Sensors in Upcoming 5G Networks

Upcoming 5G-based communication networks will be confronted with huge increases in the amount of transmitted sensor data related to massive deployments of static and mobile Internet of Things (IoT) systems. Cars acting as mobile sensors will become important data sources for cloud-based applications like predictive maintenance and dynamic traffic forecast. Due to the limitation of available communication resources, it is expected that the grows in Machine-Type Communication (MTC) will cause severe interference with Human-to-human (H2H) communication. Consequently, more efficient transmission methods are highly required. In this paper, we present a probabilistic scheme for efficient transmission of vehicular sensor data which leverages favorable channel conditions and avoids transmissions when they are expected to be highly resource-consuming. Multiple variants of the proposed scheme are evaluated in comprehensive realworld experiments. Through machine learning based combination of multiple context metrics, the proposed scheme is able to achieve up to 164% higher average data rate values for sensor applications with soft deadline requirements compared to regular periodic transmission.Comment: Best Student Paper Awar

Spin Physics at COMPASS

The COMPASS experiment is a fixed target experiment at the CERN SPS using muon and hadron beams for the investigation of the spin structure of the nucleon and hadron spectroscopy. The main objective of the muon physics program is the study of the spin of the nucleon in terms of its constituents, quarks and gluons. COMPASS has accumulated data during 6 years scattering polarized muons off a longitudinally or a transversely polarized deuteron (6LiD) or proton (NH3) target. Results for the gluon polarization are obtained from longitudinal double spin cross section asymmetries using two different channels, open charm production and high transverse momentum hadron pairs, both proceeding through the photon-gluon fusion process. Also, the longitudinal spin structure functions of the proton and the deuteron were measured in parallel as well as the helicity distributions for the three lightest quark flavors. With a transversely polarized target, results were obtained with proton and deuteron targets for the Collins and Sivers asymmetries for charged hadrons as well as for identified kaons and pions. The Collins asymmetry is sensitive to the transverse spin structure of the nucleon, while the Sivers asymmetry reflects correlations between the quark transverse momentum and the nucleon spin. Recently, a new proposal for the COMPASS II experiment was accepted by the CERN SPS which includes two new topics: Exclusive reactions like DVCS and DVMP using the muon beam and a hydrogen target to study generalized parton distributions and Drell-Yan measurements using a pion beam and a polarized NH3 target to study transverse momentum dependent distributions.Comment: Proceedings of the Rutherford conference, Manchester, August 2011. Changes due to referees comments implemente

Seamless Integration of Group Communication into an Adaptive Online Exercise System

Distance learners in traditional online exercise and tutoring systems often get stuck with questions for which they need the help of a tutor or colleague. Learning alone can also be frustrating. In our Communication And Tutoring System CATS we have integrated the possibility to dial up a tutor and/or to setup an immediate group communication with other distance learners using Internet videoconferencing technology. To find the appropriate partner, we have implemented a measurement algorithm that keeps track of the performance level of a learner by measuring the percentage of correct answers at the current level, the reliability with which the learner answers the questions and the time he/she takes. From these measures we derive a unified performance parameter that controls the presentation of the next set of questions. These are then generated dynamically by the exercise applet. The CATS system automatically selects the most appropriate communica-tion partner(s) bas! ed on the exercises the learners are currently working on, and on their skill levels. We motivate this approach from a pedagogical point of view and present the architecture and implementation of the CATS system

Ein Kommunikations- und Tutoring-System für Lerngruppen im Internet

In der klassischen Lehre spielen Übungen eine entscheidende Rolle für den Lernerfolg der Studierenden. Insbesondere Gruppenübungen ermöglichen es, einen Wissensgegenstand aus unterschiedlichen Perspektiven zu betrachten und durch das Mittel der Externalisierung besser zu verstehen. Dies setzt allerdings eine direkte Kommunikation zwischen den beteiligten Personen voraus. Im Bereich der Fernlehre sind diese Möglichkeiten aufgrund der räumlichen Trennung und der technischen Gegebenheiten nur sehr eingeschränkt gegeben. Zum einen existieren entsprechende Systeme nur für Teilaspekte, zum anderen fehlen bisher adaptive integrierte Gruppenübungen. Das in dieser Arbeit vorgestellte Communication and Tutoring System (CATS) integriert zum einen adaptive Aufgaben mit einem standardisierten Kommunikationssystem und ermöglicht dadurch die Vermittlung von Wissen zwischen den Studierenden untereinander und zwischen Studierenden und Lehrenden. Zum anderen wird ein generischer Ansatz zur technischen Abwicklung von Gruppenarbeiten in der Fernlehre vorgestellt. Sowohl die adaptiven individuellen Übungsaufgaben wie auch das Gruppenarbeitskonzept sind in verschiedenen Fächern einsetzbar. Entsprechende Hilfsprogramme unterstützen die Lehrenden bei der Erstellung von Übungsaufgaben, besondere Programmierkenntnisse sind hierzu nicht erforderlich. Damit wurde Forderungen aus der Lernpsychologie Rechnung getragen, die bisher, insbesondere im Bereich der Fernlehre, nicht erfüllt werden konnten. Bereits bei der Architektur des Systems wurde darauf geachtet, eine stabile, nachhaltige Umsetzung des Systems zu gewährleisten, ohne auf eine notwendige Flexibilität zu verzichten. Ein spezielles Integrationsmodell ermöglicht die rasche Anbindung an bestehende Lernplattformen. Im Rahmen dieser Arbeit wurde die Anbindung an die Lernplattform ".LRN" realisiert. Das Communication and Tutoring System (CATS) wurde im aktiven Übungsbetrieb zur Unterstützung der Vorlesung Rechnernetze an der Universität Mannheim in den Sommersemestern 2003 und 2004 und auch für die Vorlesung Multimediatechnik im Wintersemester 2003/04 eingesetzt. Es werden die Ergebnisse einer empirischen Untersuchung präsentiert, die zum WS 2003/04 im Rahmen der Vorlesung Multimediatechnik durchgeführt wurde. Diese betraf sowohl die Akzeptanz des Systems bei den Studierenden wie auch die Klausurergebnisse der CATS-Benutzer. Zudem werden die Examensergebnisse von Präsenzstudierenden der Rechnernetze-Vorlesung im SS 2004 mit denen der Fernstudierenden verglichen. CATS wurde außerdem in den Projekten ULI, VIROR, Winfoline und Politikon erfolgreich eingesetzt

Replicability and comprehensibility of social research and its technical implementation

"This paper is a contribution to the methodological and technical discussion of social research infrastructure. The main question is how to store and manage data in a way that meets the increasing demand for secondary data analysis in both quantitative and qualitative social science research. The first two sections focus mainly on aspects of data documentation, in particular on the unification of various documentation requirements that have arisen across ongoing projects of the SFB 882. While the aim of documenting quantitative research processes is to ensure replicability, the aim of documenting qualitative projects is to maintain the understandability and informative value of research data. In the third section a virtual research environment (VRE) is presented that provides both a generic work platform and a project-specific research platform. The work platform bundles IT resources by bringing together various tools for administration, project management, and time- and location-independent collaboration in a single environment adapted to researchers' specific work processes. The research component combines data management with further developments in social science methodologies. It provides services for the archiving and reuse of data and enables the infrastructural and methodological coordination of data documentation. We also introduce a documentation scheme for qualitative and quantitative social research within the SFB 882. This scheme considers the specific requirements of research projects within the SFB, such as different methods (e.g. panel analysis, experimental approaches, ethnography, and interview research), project work, and requirements of longterm research." (author's abstract

Untersuchungen zur Differenzierung von cerebellären Purkinjezellen nach Überexpression des Transkriptionsfaktors Engrailed-2

In dem transgenen Mausmodell L7En-2 wird der Transkriptionsfaktor Engrailed-2 in Purkinjezellen des Kleinhirns spezifisch überexprimiert. Als Folge sterben 40% dieser Zellen in der frühen Postnatalphase ab, ausserdem entwickeln sich die Dendritenbäume nur vermindert und die Monolayerbildung ist verzögert. Das Absterben der Zellen und die verminderte Dendritogenese finden auch in organotypischen Schnittkulturen statt. Zwar scheinen Wegfindung und Reifung der Axone von L7En-2 Purkinjezellen nicht beeinträchtigt zu sein, allerdings bilden sich im proximalen Abschnitt der Axone regelmässig Auftreibungen, die dornfortsatzähnliche Strukturen tragen. Elektronenmikroskopisch und immunhistochemisch konnte gezeigt werden, dass am axonalen Pol der Purkinjezellsomata Mikrotubuli, Golgi-Apparat und Ribosomen nicht in ihrer typischen Anordnung sondern ungeordnet vorliegen. Darüberhinaus konnten elektronenmikroskopisch in dieser Region zahlreiche Synapsen tragende Dornfortsätze identifiziert werden, die Ultrastruktur des axonalen Pols ähnelte also der eines Dendriten. Insgesamt weisen die Ergebnisse darauf hin, dass Engrailed-2 ein wichtiger Faktor bei der Bildung subzellulärer Kompartimente ist und, dass die physiologische Herunterregulation von Engrailed-2 in früh postnatalen Purkinjezellen wichtig für ein Umschalten vom axonalen zum dendritischen Wachstumsmodus ist.Effects of Engrailed-2 overexpression on the differentiation of cerebellar Purkinje cells In the transgenic mouse model L7En-2, the transcription factor Engrailed-2 is specifically overexpressed in cerebellar Purkinje cells. As a consequence, 40% of Purkinje cells are lost during early postnatal development, and the dendritic arborization and monolayer formation is markedly retarded. In organotypic slice cultures, altered cell loss and dendritogenesis is recapitulated. While axonal pathfinding and maturation does not seem to be affected in L7En-2 Purkinje cells, they develop large swellings in the proximal part of their axons, often carrying spine-like structures. Electron microscopy and immunohistochemical stainings revealed an unorganized distribution of microtubules, Golgi stacks and ribosomes at the axonal somatic pole of Purkinje cells. In addition, a massive accumulation of spines containing synapses can be observed at the axonal pole, reminding of dendritic ultrastructure. The outlined findings suggest that Engrailed-2 is involved in processes underlying the establishment of cellular compartmentation and that physiological downregulation of Engrailed-2 during perinatal development is important for the switch from the axonal to the dendritic growth mode

Machine learning based context-predictive car-to-cloud communication using multi-layer connectivity maps for upcoming 5G networks

While cars were only considered as means of personal transportation for a long time, they are currently transcending to mobile sensor nodes that gather highly up-to-date information for crowdsensing-enabled big data services in a smart city context. Consequently, upcoming 5G communication networks will be confronted with massive increases in Machine-type Communication (MTC) and require resource-efficient transmission methods in order to optimize the overall system performance and provide interference-free coexistence with human data traffic that is using the same public cellular network. In this paper, we bring together mobility prediction and machine learning based channel quality estimation in order to improve the resource-efficiency of car-to-cloud data transfer by scheduling the transmission time of the sensor data with respect to the anticipated behavior of the communication context. In a comprehensive field evaluation campaign, we evaluate the proposed context-predictive approach in a public cellular network scenario where it is able to increase the average data rate by up to 194% while simultaneously reducing the mean uplink power consumption by up to 54%