66 resultados para Map Cube
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Kartta kuuluu A. E. Nordenskiöldin kokoelmaan
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Kartta kuuluu A. E. Nordenskiöldin kokoelmaan
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Kartta kuuluu A. E. Nordenskiöldin kokoelmaan
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Kartta kuuluu A. E. Nordenskiöldin kokoelmaan
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[N. 1:8500000].
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Kahdessa osassa painettu kartta.
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0-meridiaani: Lontoo. - Koordinaattiasteikko: N90°-55°[50°].
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1:4000.
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This literature review aims to clarify what is known about map matching by using inertial sensors and what are the requirements for map matching, inertial sensors, placement and possible complementary position technology. The target is to develop a wearable location system that can position itself within a complex construction environment automatically with the aid of an accurate building model. The wearable location system should work on a tablet computer which is running an augmented reality (AR) solution and is capable of track and visualize 3D-CAD models in real environment. The wearable location system is needed to support the system in initialization of the accurate camera pose calculation and automatically finding the right location in the 3D-CAD model. One type of sensor which does seem applicable to people tracking is inertial measurement unit (IMU). The IMU sensors in aerospace applications, based on laser based gyroscopes, are big but provide a very accurate position estimation with a limited drift. Small and light units such as those based on Micro-Electro-Mechanical (MEMS) sensors are becoming very popular, but they have a significant bias and therefore suffer from large drifts and require method for calibration like map matching. The system requires very little fixed infrastructure, the monetary cost is proportional to the number of users, rather than to the coverage area as is the case for traditional absolute indoor location systems.
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Advancements in information technology have made it possible for organizations to gather and store vast amounts of data of their customers. Information stored in databases can be highly valuable for organizations. However, analyzing large databases has proven to be difficult in practice. For companies in the retail industry, customer intelligence can be used to identify profitable customers, their characteristics, and behavior. By clustering customers into homogeneous groups, companies can more effectively manage their customer base and target profitable customer segments. This thesis will study the use of the self-organizing map (SOM) as a method for analyzing large customer datasets, clustering customers, and discovering information about customer behavior. Aim of the thesis is to find out whether the SOM could be a practical tool for retail companies to analyze their customer data.
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Teoksessa: A Complete System of Geography /E. Bowen, 1747. Plate 27.
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0-meridiaani Lontoo: Koordinaattiasteikko: W15°-E85°, N74°30'-48°.
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London, published by James Wyld, Geographer to the Queen & H.R.H. Prince Albert, Charing Cross East & Model of the Earth, Leicester Square.
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Kartta leikattu karttakuvaa reunastavan kehyksen ulkorajaa pitkin.