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Auflistung nach Autor:in "Niklasson, Lars"

1 - 3 von 3
  • Konferenzbeitrag
    Trajectory Clustering and Coastal Surveillance
    (Informatik 2007 – Informatik trifft Logistik – Band 2, 2007) Dahlbom, Anders; Niklasson, Lars
    In this paper we explore trajectory clustering as a means for representing the normal behavior of vessels in a coastal surveillance scenario. Trajectory clustering however suffers from some drawbacks in this type of setting and we therefore propose a new approach, spline-based clustering, with a potential for solving the task of representing the normal course of events.
  • Konferenzbeitrag
    Uncertainty measures for sensor management in a survivability application
    (INFORMATIK 2011 – Informatik schafft Communities, 2011) Erlandsson, Tina; Niklasson, Lars
    When flying a mission, a fighter pilot is exposed to the risk of being hit by enemy fire. A tactical support system can aid the pilot by calculating the survivability of a given route, which is the probability that the fighter pilot can fly the route without being hit. The survivability estimate will be uncertain due to uncertainty in the information about threats in the area. In this paper, we investigate the uncertainty in the estimate of the survivability and compare two different measures of uncertainty; standard deviation and entropy. Furthermore, we discuss how these measures can be used for sensor management and discuss a few issues that need to be addressed in the design of a sensor management system in a fighter aircraft.
  • Konferenzbeitrag
    A Unified Situation Analysis Model for Human and Machine Situation Awareness
    (Informatik 2007 – Informatik trifft Logistik – Band 2, 2007) Niklasson, Lars; Riveiro, Maria; Johansson, Fredrik; Dahlbom, Anders; Falkman, Göran; Ziemke, Tom; Brax, Christoffer; Kronhamn, Thomas; Smedberg, Martin; Warston, Håkan; Gustavsson, Per M.
    The use of technology to assist human decision making is not a novel idea. However, we argue that there is a need for a unified model which synthesizes and extends existing models. In this paper, we give two perspectives on situation analysis: a technological perspective and a human perspective. These two perspectives are merged into a unified situation analysis model for semi-automatic, automatic and manual decision support (SAM)2.