@article{AzodiChengMeinel2015,
  author    = {Azodi, Amir and Cheng, Feng and Meinel, Christoph},
  title     = {Event Driven Network Topology Discovery and Inventory Listing Using REAMS},
  series = {Wireless personal communications : an international journal},
  volume    = {94},
  journal   = {Wireless personal communications : an international journal},
  publisher = {Springer},
  address   = {New York},
  issn      = {0929-6212},
  doi       = {10.1007/s11277-015-3061-3},
  pages     = {415 -- 430},
  year      = {2015},
  abstract  = {Network Topology Discovery and Inventory Listing are two of the primary features of modern network monitoring systems (NMS). Current NMSs rely heavily on active scanning techniques for discovering and mapping network information. Although this approach works, it introduces some major drawbacks such as the performance impact it can exact, specially in larger network environments. As a consequence, scans are often run less frequently which can result in stale information being presented and used by the network monitoring system. Alternatively, some NMSs rely on their agents being deployed on the hosts they monitor. In this article, we present a new approach to Network Topology Discovery and Network Inventory Listing using only passive monitoring and scanning techniques. The proposed techniques rely solely on the event logs produced by the hosts and network devices present within a network. Finally, we discuss some of the advantages and disadvantages of our approach.},
  language  = {en}
}
@article{GruenewaldMeinel2015,
  author    = {Gr{\"u}newald, Franka and Meinel, Christoph},
  title     = {Implementation and Evaluation of Digital E-Lecture Annotation in Learning Groups to Foster Active Learning},
  series = {IEEE transactions on learning technologies},
  volume    = {8},
  journal   = {IEEE transactions on learning technologies},
  number    = {3},
  publisher = {Inst. of Electr. and Electronics Engineers},
  address   = {Los Alamitos},
  issn      = {1939-1382},
  doi       = {10.1109/TLT.2015.2396042},
  pages     = {286 -- 298},
  year      = {2015},
  abstract  = {The use of video lectures in distance learning involves the two major problems of searchability and active user participation. In this paper, we promote the implementation and usage of a collaborative educational video annotation functionality to overcome these two challenges. Different use cases and requirements, as well as details of the implementation, are explained. Furthermore, we suggest more improvements to foster a culture of participation and an algorithm for the extraction of semantic data. Finally, evaluations in the form of user tests and questionnaires in a MOOC setting are presented. The results of the evaluation are promising, as they indicate not only that students perceive it as useful, but also that the learning effectiveness increases. The combination of personal lecture video annotations with a semantic topic map was also evaluated positively and will thus be investigated further, as will the implementation in a MOOC context.},
  language  = {en}
}