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  • 1.
    Pappas, Nikolaos
    et al.
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Gunnarsson, Johan
    Linköping University, Department of Behavioural Sciences and Learning. Linköping University, Faculty of Arts and Sciences.
    Kratz, Ludvig
    Linköping University, Department of Science and Technology. Linköping University, Faculty of Science & Engineering.
    Kountouris, Marios
    Huawei Technology Co Ltd, Peoples R China.
    Angelakis, Vangelis
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Age of Information of Multiple Sources with Queue Management2015In: 2015 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), IEEE , 2015, p. 5935-5940Conference paper (Refereed)
    Abstract [en]

    We consider a system of multiple sources generating status update packets, which need to be sent by a single transmitter to a destination over a network. In the model we study, the packet generation time may vary at each source, and the packets go through the network with a random delay. Each update carries a time stamp of its generation, allowing the destination to calculate for each source the so called Age of Information, which measures the timeliness of each status update arriving. Considering that queuing delay can unnecessarily increase the age of a critical status update, we propose here a queue management technique, in which we maintain a queue with only the latest status packet of each source, overwriting any previously queued update from that source. This simple technique drastically limits the need for buffering and can be applied in systems where the history of source status is not relevant. We show that this scheme results in significantly less transmissions compared to the standard M/M/1 queue model. Furthermore, the proposed technique reduces the per source age of information, especially in settings not using queue management with high status update generation rates.

  • 2.
    Rudner, Mary
    et al.
    Linköping University, The Swedish Institute for Disability Research. Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences.
    Karlsson, Thomas
    Linköping University, The Swedish Institute for Disability Research. Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences.
    Gunnarsson, Johan
    Linköping University, The Swedish Institute for Disability Research. Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences.
    Rönnberg, Jerker
    Linköping University, The Swedish Institute for Disability Research. Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences.
    Levels of processing and language modality specificity in working memory2013In: Neuropsychologia, ISSN 0028-3932, E-ISSN 1873-3514, Vol. 51, no 4, p. 656-666Article in journal (Refereed)
    Abstract [en]

    Neural networks underpinning working memory demonstrate sign language specific components possibly related to differences in temporary storage mechanisms. A processing approach to memory systems suggests that the organisation of memory storage is related to type of memory processing as well. In the present study, we investigated for the first time semantic, phonological and orthographic processing in working memory for sign- and speech-based language. During fMRI we administered a picture-based 2-back working memory task with Semantic, Phonological, Orthographic and Baseline conditions to 11 deaf signers and 20 hearing non-signers. Behavioural data showed poorer and slower performance for both groups in Phonological and Orthographic conditions than in the Semantic condition, in line with depth-of-processing theory. An exclusive masking procedure revealed distinct sign-specific neural networks supporting working memory components at all three levels of processing. The overall pattern of sign-specific activations may reflect a relative intermodality difference in the relationship between phonology and semantics influencing working memory storage and processing.

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