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  • 1.
    Bååth, Rasmus
    et al.
    Lund University Cognitive Science, Lund University, LUX, Lund, Sweden.
    Lagerstedt, Erik
    Lund University Cognitive Science, Lund University, LUX, Lund, Sweden.
    Gärdenfors, Peter
    Lund University Cognitive Science, Lund University, LUX, Lund, Sweden.
    A prototype-based resonance model of rhythm categorization2014In: i-Perception, ISSN 2041-6695, E-ISSN 2041-6695, Vol. 5, no 6, p. 548-558Article in journal (Refereed)
    Abstract [en]

    Categorization of rhythmic patterns is prevalent in musical practice, an example of this being the transcription of (possibly not strictly metrical) music into musical notation. In this article we implement a dynamical systems' model of rhythm categorization based on the resonance theory of rhythm perception developed by Large (2010). This model is used to simulate the categorical choices of participants in two experiments of Desain and Honing (2003). The model accurately replicates the experimental data. Our results support resonance theory as a viable model of rhythm perception and show that by viewing rhythm perception as a dynamical system it is possible to model central properties of rhythm categorization.

  • 2.
    Bååth, Rasmus
    et al.
    Lund University Cognitive Science.
    Lagerstedt, Erik
    Lund University Cognitive Science.
    Gärdenfors, Peter
    Lund University Cognitive Science.
    An Oscillator Model of Categorical Rhythm Perception2013In: Cooperative Minds: Social Interaction and Group Dynamics: Proceedings of the 35th Annual Meeting of the Cognitive Science Society, Berlin, Germany, July 31-August 3, 2013 / [ed] Markus Knauff, Natalie Sebanz, Michael Pauen, Ipke Wachsmuth, Austin, TX: Cognitive Science Society, Inc., 2013, p. 1803-1808Conference paper (Refereed)
    Abstract [en]

    Categorical perception is a well studied phenomenon in, for example, colour perception, phonetics and music. In this article we implement a dynamical systems model of categorical rhythm perception based on the resonance theory of rhythm perception developed by Large (2010). This model is used to simulate the categorical choices of participants in two experiments of Desain and Honing (2003). The model is able to accurately replicate the experimental data. Our results supports that resonance theory is a viable model of rhythm perception and they show that by viewing rhythm perception as a dynamical system it is possible to model properties of categorical perception.

  • 3.
    Frykholm, K.
    et al.
    Department of Biology and Biological Engineering, Chalmers University of Technology.
    Nyberg, L. K.
    Department of Biology and Biological Engineering, Chalmers University of Technology.
    Lagerstedt, Erik
    Department of Astronomy and Theoretical Physics, Lund University.
    Noble, C.
    Department of Astronomy and Theoretical Physics, Lund University.
    Fritzsche, J.
    Department of Applied Physics, Chalmers University of Technology.
    Karami, N.
    Department of Clinical Microbiology, Sahlgrenska University Hospital and Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy of the University of Gothenburg.
    Ambjörnsson, T.
    Department of Astronomy and Theoretical Physics, Lund University.
    Sandegren, L.
    Department of Medical Biochemistry and Microbiology, Uppsala University.
    Westerlund, F.
    Department of Biology and Biological Engineering, Chalmers University of Technology.
    Fast size-determination of intact bacterial plasmids using nanofluidic channels2015In: Lab on a Chip, ISSN 1473-0197, E-ISSN 1473-0189, Vol. 15, no 13, p. 2739-2743Article in journal (Refereed)
    Abstract [en]

    We demonstrate how nanofluidic channels can be used as a tool to rapidly determine the number and sizes of plasmids in bacterial isolates. Each step can be automated at low cost, opening up opportunities for general use in microbiology labs.

  • 4.
    Kolbeinsson, Ari
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Lagerstedt, Erik
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindblom, Jessica
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Classification of Collaboration Levels for Human-Robot Cooperation in Manufacturing2018In: Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018,  University of Skövde, Sweden / [ed] Peter Thorvald, Keith Case, Amsterdam: IOS Press, 2018, p. 151-156Conference paper (Refereed)
    Abstract [en]

    Industry 4.0 aims to support the factory of the future, which involves increased amounts of information systems and new ways of using automation. One new usage is collaboration between human and industrial robot in manufacturing, with both partners sharing work on a single task. Supporting human-robot collaboration (HRC) requires understanding the requirements of HRC as well as the differences to existing approaches where the goal is more automation, such as in the case of self-driving cars. We propose a framework that we call levels of collaboration to support this, and posit that this framework supports a mental model conducive to the design of lines incorporating HRC.

  • 5.
    Kolbeinsson, Ari
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Lagerstedt, Erik
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindblom, Jessica
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Foundation for a classification of collaboration levels for human-robot cooperation in manufacturing2019In: Production & Manufacturing Research, ISSN 2169-3277, Vol. 7, no 1, p. 448-471Article in journal (Refereed)
    Abstract [en]

    Industry 4.0 aims to support the factory of the future, involving increased use of information systems and new ways of using automation, such as collaboration where a robot and a human share work on a single task. We propose a classification of collaboration levels for Human-Robot collaboration (HRC) in manufacturing that we call levels of collaboration (LoC), formed to provide a conceptual model conducive to the design of assembly lines incorporating HRC. This paper aims to provide a more theoretical foundation for such a tool based on relevant theories from cognitive science and other perspectives of human-technology interaction, strengthening the validity and scientific rigour of the envisioned LoC tool. The main contributions consist of a theoretical grounding to motivate the transition from automation to collaboration, which are intended to facilitate expanding the LoC classification to support HRC, as well as an initial visualization of the LoC approach. Future work includes fully defining the LoC classification as well as operationalizing functionally different cooperation types. We conclude that collaboration is a means to an end, so collaboration is not entered for its own sake, and that collaboration differs fundamentally from more commonly used views where automation is the focus.

  • 6.
    Lagerstedt, Erik
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Riveiro, Maria
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Thill, Serge
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. Plymouth University, United Kingdom.
    Agent Autonomy and Locus of Responsibility for Team Situation Awareness2017In: HAI '17: Proceedings of the 5th International Conference on Human Agent Interaction, New York: Association for Computing Machinery (ACM), 2017, p. 261-269Conference paper (Refereed)
    Abstract [en]

    Rapid technical advancements have led to dramatically improved abilities for artificial agents, and thus opened up for new ways of cooperation between humans and them, from disembodied agents such as Siris to virtual avatars, robot companions, and autonomous vehicles. It is therefore relevant to study not only how to maintain appropriate cooperation, but also where the responsibility for this resides and/or may be affected. While there are previous organisations and categorisations of agents and HAI research into taxonomies, situations with highly responsible artificial agents are rarely covered. Here, we propose a way to categorise agents in terms of such responsibility and agent autonomy, which covers the range of cooperation from humans getting help from agents to humans providing help for the agents. In the resulting diagram presented in this paper, it is possible to relate different kinds of agents with other taxonomies and typical properties. A particular advantage of this taxonomy is that it highlights under what conditions certain effects known to modulate the relationship between agents (such as the protégé effect or the "we"-feeling) arise.

  • 7.
    Lagerstedt, Erik
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Riveiro, Maria
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Thill, Serge
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Interacting with Artificial Agents2015In: Thirteenth Scandinavian Conference on Artificial Intelligence / [ed] Sławomir Nowaczyk, IOS Press, 2015, Vol. 278, p. 184-185Conference paper (Refereed)
  • 8.
    Lagerstedt, Erik
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Svensson, Henrik
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    A drive through the world of functional tones, simulations and cars2017In: Proceedings of the 13th SweCog Conference / [ed] Anders Arweström Jansson, Anton Axelsson, Rebecca Andreasson, Erik Billing, 2017, p. 12-14Conference paper (Refereed)
  • 9.
    Lagerstedt, Erik
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Thill, Serge
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Perception of Agent Properties in Humans and Machines2018Conference paper (Refereed)
  • 10.
    Nyberg, Lena K.
    et al.
    Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Quaderi, Saair
    Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden / Department of Astronomy and Theoretical Physics, Lund University, Lund, Sweden.
    Emilsson, Gustav
    Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden / Department of Applied Physics, Chalmers University of Technology, Gothenburg, Sweden.
    Karami, Nahid
    Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Lagerstedt, Erik
    Department of Astronomy and Theoretical Physics, Lund University, Lund, Sweden.
    Müller, Vilhelm
    Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Noble, Charleston
    Department of Astronomy and Theoretical Physics, Lund University, Lund, Sweden.
    Hammarberg, Susanna
    Department of Astronomy and Theoretical Physics, Lund University, Lund, Sweden.
    Nilsson, Adam N.
    Department of Astronomy and Theoretical Physics, Lund University, Lund, Sweden.
    Sjöberg, Fei
    Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
    Fritzsche, Joachim
    Department of Applied Physics, Chalmers University of Technology, Gothenburg, Sweden.
    Kristiansson, Erik
    Department of Mathematical Sciences, Chalmers University of Technology, University of Gothenburg, Gothenburg, Sweden.
    Sandegren, Linus
    Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
    Ambjörnsson, Tobias
    Department of Astronomy and Theoretical Physics, Lund University, Lund, Sweden.
    Westerlund, Fredrik
    Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Rapid identification of intact bacterial resistance plasmids via optical mapping of single DNA molecules2016In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 6, article id 30410Article in journal (Refereed)
    Abstract [en]

    The rapid spread of antibiotic resistance - currently one of the greatest threats to human health according to WHO - is to a large extent enabled by plasmid-mediated horizontal transfer of resistance genes. Rapid identification and characterization of plasmids is thus important both for individual clinical outcomes and for epidemiological monitoring of antibiotic resistance. Toward this aim, we have developed an optical DNA mapping procedure where individual intact plasmids are elongated within nanofluidic channels and visualized through fluorescence microscopy, yielding barcodes that reflect the underlying sequence. The assay rapidly identifies plasmids through statistical comparisons with barcodes based on publicly available sequence repositories and also enables detection of structural variations. Since the assay yields holistic sequence information for individual intact plasmids, it is an ideal complement to next generation sequencing efforts which involve reassembly of sequence reads from fragmented DNA molecules. The assay should be applicable in microbiology labs around the world in applications ranging from fundamental plasmid biology to clinical epidemiology and diagnostics.

  • 11.
    Thill, Serge
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Riveiro, Maria
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lagerstedt, Erik
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lebram, Mikael
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Hemeren, Paul
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Habibovic, Azra
    Research Institutes of Sweden, RISE Viktoria, Lindholmen Science Park, Göteborg, Sweden.
    Klingegård, Maria
    Research Institutes of Sweden, RISE Viktoria, Lindholmen Science Park, Göteborg, Sweden.
    Driver adherence to recommendations from support systems improves if the systems explain why they are given: A simulator study2018In: Transportation Research Part F: Traffic Psychology and Behaviour, ISSN 1369-8478, E-ISSN 1873-5517, Vol. 56, p. 420-435Article in journal (Refereed)
    Abstract [en]

    This paper presents a large-scale simulator study on driver adherence to recommendationsgiven by driver support systems, specifically eco-driving support and navigation support.123 participants took part in this study, and drove a vehicle simulator through a pre-defined environment for a duration of approximately 10 min. Depending on the experi-mental condition, participants were either given no eco-driving recommendations, or asystem whose provided support was either basic (recommendations were given in theform of an icon displayed in a manner that simulates a heads-up display) or informative(the system additionally displayed a line of text justifying its recommendations). A naviga-tion system that likewise provided either basic or informative support, depending on thecondition, was also provided.

    Effects are measured in terms of estimated simulated fuel savings as well as engine brak-ing/coasting behaviour and gear change efficiency. Results indicate improvements in allvariables. In particular, participants who had the support of an eco-driving system spenta significantly higher proportion of the time coasting. Participants also changed gears atlower engine RPM when using an eco-driving support system, and significantly more sowhen the system provided justifications. Overall, the results support the notion that pro-viding reasons why a support system puts forward a certain recommendation improvesadherence to it over mere presentation of the recommendation.

    Finally, results indicate that participants’ driving style was less eco-friendly if the navi-gation system provided justifications but the eco-system did not. This may be due to par-ticipants considering the two systems as one whole rather than separate entities withindividual merits. This has implications for how to design and evaluate a given driver sup-port system since its effectiveness may depend on the performance of other systems in thevehicle.

1 - 11 of 11
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