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Table 3 also shows that fewer students enrol at the second enrolment point in the academic year (February) and so fewer runs need to be made. Table 4, which again focuses on the Introduction to Psychology course, shows dramatically fewer runs than for the same enrolment period yet with a similar number of students.
"... In PAGE 12: ... As a result thresholds have been introduced for group size and some cities are associated with more than one run (eg Amsterdam, Zwolle, Rotterdam, Den Haag for September 2003). Unit of Learning Run date Run identifier Number of Students Leuven 17 Kortrijk 9 Gent 60 Diepenbeek 60 Brussel 4 Vlissingen 28 Antwerpe 69 Leeuwarden 36 Emmen 18 Zwolle 1 38 Zwolle 2 38 Utrecht 2 78 Utrecht 1 77 Sittard 72 Rotterdam 2 71 Rotterdam 1 71 Nijmegen 108 Groningen 77 Enschede 42 Eindhoven 100 Den Haag 2 57 Breda 71 Amsterdam 2 109 Amsterdam 1 108 Den Haag 1 56 September 2003 Alkmaar 61 Gent 38 Vlissingen 17 Leuven 13 Kortrijk 5 Diepenbeek 31 Antwerpen 58 Brussel 2 Zwolle 47 Utrecht 16 Sittard 40 Rotterdam 82 Nijmegen 57 Groningen 75 Enschede 20 Eindhoven 50 Den Haag 65 Breda 39 Introduction to Psychology February 2004 Amsterdam 110 Table3 . E-learning courses (units of learning) with multiple runs ... ..."
Table 2: The level of automation aimed at the work of e-contracting research domains DEEP E-CONTRACTING RESEARCH DOMAIN SHALLOW E- CONTRACTING
"... In PAGE 81: ... Table 1: The work of the e-contracting research domains positioned in the 4W framework RESEARCH DOMAIN WHO WHERE WHAT HOW 4 Queensland University and Distributed Systems Technology Centre (DSTC) x x X 5 University of St. Gallen x x x x 6 Twente University and Eindhoven University of Technology x x X X 7 IBM Research Division x x X X 8 Hewlett-Packard Laboratories x X 9 University of Hamburg x x X X 10 Tilburg University X x 11 Hong Kong University of Science and Technology and Chinese University of Honk Kong x x 12 King apos;s College London, Brunel University, and Imperial College of Science, Technology and Medicine X X Next, in Table2 , we present the level and area of automation aimed in the work of the e-... ..."
Table 1: Data sample from the LML sensor network. School children can analyze these data to determine the environmental consequences of releasing air pollutants to the environment. For example, acid rain occurs when emissions of sulfur dioxide (SO2) and oxides of nitrogen (NOx) in the atmosphere react with water and air pollutants to form acidic compounds.
2005
"... In PAGE 7: ...vii Table of Tables Table1 : Data sample from the LML sensor network. School children can analyze these data to determine the environmental consequences of releasing air pollutants to the environment.... In PAGE 7: ...able 9: XML Schema for LML Sensor Data........................................................34 Table1 0: XML representation of sensor data sample given in Table 8.... In PAGE 7: ...able 10: XML representation of sensor data sample given in Table 8. ...............35 Table1 1: Metadata describes semantics of concentrations measured via LML sensor network.... In PAGE 7: ...ensor network. ......................................................................................................36 Table1 2: Metadata describes physical location of some LML stations where concentrations are measured.... In PAGE 10: ... The goal of Virtual School Lab is to make data available and usable for educational purposes allowing school children to retrieve and query sensor data promptly and effectively. Table1 shows an example of sensor data collected from the LML sensor network. When properly processed and presented, these data can be used by school children to analyze the quality of the air at different places in the Netherlands.... In PAGE 15: ... There are existing sets of sensor data that could be exploited for education. For example, the LML network generates data related with the quality of the air at different places in the Netherlands (see Table1 ). Virtual School Lab makes these data available to school children for educational purposes.... In PAGE 42: ...35 Table1 0: XML representation of sensor data sample given in Table 8. 4.... In PAGE 43: ...etwork. This information is made available to the users via SDMS. Metadata is encoded in XHTML format and presented to the users in regular HTML tables. Property Description Type Unit Scale Resolution SO2 Sulfur Dioxide integer ug/m3 1 1 PM10 Particulate Matter integer ug/m3 1 1 NH3 Ammonia integer ug/m3 1 1 CO Carbon Monoxide integer ug/m3 1 1 O3 Ozone integer ug/m3 1 1 N0 Nitric Oxide integer ug/m3 1 1 N02 Nitrogen Dioxide integer ug/m3 1 1 Table1 1: Metadata describes semantics of concentrations measured via LML sensor network. Table 12 contains metadata that describes the physical location of different stations of LML sensor network.... In PAGE 43: ... Table 12 contains metadata that describes the physical location of different stations of LML sensor network. StationID Location Type Coordinates 136 Heerlen-Looierstraat Street none 236 Eindhoven-Genovevalaan Street none 237 Eindhoven-Noordbrabantlaan Street none 240 Breda-Tilburgseweg Street none 433 Vlaardingen-Floreslaan Street none 445 Den Haag-Veerkade Street none 447 Leiden-Willem de Zwijgerlaan Street none 448 Rotterdam-Statenweg Street none 537 Haarlem-Amsterdamsevaart Street none 544 Amsterdam-Bernhardplein Street none 636 Utrecht-de Jongweg Street none 638 Utrecht-Vleutenseweg Street none 639 Utrecht-Erzeijstraat Street none 641 Breukelen-Snelweg Street none 741 Nijmegen-Graafseweg Street none 937 Groningen-Europaweg Street none Table1 2: Metadata describes physical location of some LML stations where concentrations are measured. ... ..."
