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Sökning: LAR1:lu > Konferensbidrag

  • Resultat 1-10 av 24744
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  • Aamodt, K., et al. (författare)
  • Alignment of the ALICE Inner Tracking System with cosmic-ray tracks
  • 2010
  • Ingår i: Journal of Instrumentation. - IOP Publishing. - 1748-0221. ; 5
  • Konferensbidrag (refereegranskat)abstract
    • ALICE (A Large Ion Collider Experiment) is the LHC (Large Hadron Collider) experiment devoted to investigating the strongly interacting matter created in nucleus-nucleus collisions at the LHC energies. The ALICE ITS, Inner Tracking System, consists of six cylindrical layers of silicon detectors with three different technologies; in the outward direction: two layers of pixel detectors, two layers each of drift, and strip detectors. The number of parameters to be determined in the spatial alignment of the 2198 sensor modules of the ITS is about 13,000. The target alignment precision is well below 10 mu m in some cases (pixels). The sources of alignment information include survey measurements, and the reconstructed tracks from cosmic rays and from proton-proton collisions. The main track-based alignment method uses the Millepede global approach. An iterative local method was developed and used as well. We present the results obtained for the ITS alignment using about 10(5) charged tracks from cosmic rays that have been collected during summer 2008, with the ALICE solenoidal magnet switched off.
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  • Aanæs, Henrik, et al. (författare)
  • Camera Resectioning from a Box
  • 2009
  • Ingår i: Lecture Notes in Computer Science. - Springer. - 0302-9743 .- 1611-3349.
  • Konferensbidrag (refereegranskat)abstract
    • In this paper we describe how we can do camera resectioning from a box with unknown dimensions, i.e. determine the camera model, assuming that image pixels are square. This assumption is equivalent to assuming that the camera as an aspect ratio of one and zero skew, and holds for most - if not all - digital cameras. Our proposed method works by first deriving 9 linear constraints on the projective camera matrix from the box, leaving a 3 dimensional subspace in which the projective camera matrix can lye. A single solution in this 3D subspace is then found via a method by Triggs in 1999, which uses the squared pixel assumption to set up a 4th degree polynomial to which the solution is the desired model. This approach is, however, numerically challenging, and we use several means to combat this issue. Lastly the solution is refined in an iterative manner, i.e. using bundle adjustment.
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  • Aasa, Anna, et al. (författare)
  • Collecting dialect data and making use of them an interim report from Swedia 2000
  • 2000
  • Ingår i: Proceedings FONETIK 2000. - University of Gothenburg. ; s. 17-20
  • Konferensbidrag (övrigt vetenskapligt)abstract
    • This paper consists of two, somewhat disparate parts. In the first part, some experiences of two years of fieldwork are summarized, concentrating, as the subtitle suggests, on the very heart of phonetic fieldwork: the encounters and interviews with the informants. As a result of the fieldwork, the project now has access to recordings from approximately 1300 speakers of more than 100 dialects of Swedish. We are currently initiating research on various aspects of the sound patterns of these dialects. The second part of the paper is meant to give an overview of some of our research plans for the near future.
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  • Abaravicius, Juozas, et al. (författare)
  • Analysing Load Demand in Households
  • 2006
  • Ingår i: [Host publication title missing]. - EEDAL Proceedings 2006.
  • Konferensbidrag (refereegranskat)abstract
    • The importance of load demand variation, when analysing energy and environmental impact of residential energy use, is increasing. Load demand in residential houses is a significant contributor to peak load problems experienced by utilities. The knowledge about demand variation in households is limited as well as the use of methodologies to analyse the demand is. Many utilities have recently installed interval (hourly) metering at their residential customers. The availability of this data is a big step forward, however, our experience show that the utilities use this data only to a limited extent, mostly for billing purposes only. This study aims to discuss the ways and benefits of using this valuable end-use data. There are several established load analysis tools, such as load curve, typical load curve, load duration curve, load factor, superposition factor, etc., which utilities could apply and develop. Among other benefits, the hourly load data analysis can provide the detailed characteristics of load demand in households, define the consumption patterns and can help to identify the main contributors to the utility peaks. This information is essential when developing new energy services, appropriate pricing, load management strategies and demand response programs. This paper analyses strengths and weaknesses of different analysis tools, the knowledge they could give, how applicable they are and what value they could have for the utility and the customer. The study is exemplified with ten “real world” cases in Southern Sweden, where the households with electric space heating and hot water systems are analysed.
10.
  • Abaravicius, Juozas, et al. (författare)
  • More or Less about Data - Analyzing Load Demand in Residential Houses
  • 2006
  • Ingår i: [Host publication title missing]. - ACEEE.
  • Konferensbidrag (refereegranskat)abstract
    • Load demand in residential houses is a significant contributor to peak load problems experienced by utilities. The knowledge about demand variation in households is fairly limited as well as the use of various tools to analyze the demand. Many utilities have recently installed interval (hourly) metering at their residential customers. The availability of hourly data is a significant progress, however, the utilities use this data only to a limited extent, mostly for billing purposes only. This study aims to discuss the possibilities and the benefits of using this valuable data. There are several established load analysis tools, such as load curve, typical load curve, load duration curve, load factor, superposition factor, etc., which utilities could apply and develop to provide feedback to small electricity users. Among other benefits, the hourly load data analysis can provide the detailed characteristics of load demand, define the consumption patterns and can help to identify which households contribute most to the utility peaks. This information is essential when developing new energy services, appropriate pricing, load management strategies and demand response programs. Through the analysis of strengths and weaknesses of different load analysis tools, this paper defines the knowledge they could give, how applicable they are and what value they could have both for the utility and the residential customer. The study is exemplified with ten cases of households with electric space heating in Southern Sweden.
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