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Namely, even if the GPS equipment and GPS-enabled devices are becoming more common, users seldom have access to GPS information and GSM cell identi ers do not allow separating signi cant locations that are near each other (ie that are mainly covered by the same cells) In this book, a setting where GSM cell transitions are logged to enrich the information using the GPS coordinates of the transition point whenever a GPS device is available is considered The ContextWatcher application (see 7) has been used to monitor cell changes Whenever a cell change occurs, the available location information is sent to the Location Provider (see Section 414) If there is a GPS device connected to ContextWatcher, the GPS coordinates at the transition point are sent to the Location Provider.

ALCOHOL(t) (22.2)

If no GPS coordinates are provided, the Location Provider can use GPS measurements of other users to give an estimate for the GPS coordinates of the cell All in all, the setting considered results in partially incomplete data: The GSM cell identi er is almost always present, as well as country information Latitude and longitude information is present in approximately 70% of the cases, city information in 60% of the cases and street information in 50% of the cases In the data gathering effort performed, relatively many people had GPS devices available, but commonly the situation would not be as good The Location Provider is also responsible for identifying signi cant locations from the available location information In [83], four algorithms have been presented for identifying signi cant locations in the described setting.

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I simply cannot exist any longer without a midday run. The problem is that I am expected to counsel students throughout the day that s my job. . . . Part of my noon run consists of my lunch period, but I always exceed that by 30 minutes or so. . . . I know it s wrong though especially with the students waiting to see me I don t know what I m going to do. (quoted in Morgan, 1979, p. 69)

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The rst two algorithms are based on graph clustering whereas the two last are based on duration and cell transition information Also, these algorithms are variants of spatial clustering and the two last use temporal processing 4322 Symbol String Clustering In [8], a set of recorded data is analysed using exploratory data analysis and visualisation techniques, such as the Self-organizing Map (SOM) [59] The information sources used range from time and location to sensors such as air pressure, temperature and acceleration The main conclusion drawn from [8] is that high-level user contexts can be de ned as clusters in the data generated from the combination of multiple information sources For several reasons, methods like the SOM cannot be directly applied to clustering data or context awareness in a mobile device environment.

The reasons, referred to in [8], are related to the statistical distribution of the data and the limited computational and memory resources of a mobile device Another problem is related to data representation where the data comes from many different sources For example, temperature is represented as a real number and location by a discrete index (GSM cell ID) or a two dimensional vector (GPS) The question is how to.

To call a user-defined function in normal mode:

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Again, the HTML is simple:

Select a statement in the Script pane, then do one of the following:

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