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By Büchel G.

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We first used NNSS to position mobile terminals. 10 meters. Table1 shows the error distance in each position. Then we used MNNSS to position mobile terminals. For each compare, we used 2 layers. 5. MNNSS corrected the two errors and classifies all the testing positions. 47 meters. Table2 shows the error distance in each position. 11-Based Location Determination Approach for Context-Aware System 7 Table 2. 11 based location determination system. We assume that all data needed in location determination are acquired before, and we didn’t discuss how to set up APs and how to select the reference points.

We lay emphasis on the location determination algorithm. NNSS can position objects only by the received signal strength measured by each mobile terminal. This algorithm is cost-efficient, and we don’t need to apply much modification to the communicative devices in the mobile terminals and the service provider. MNNSS is a modification to NNSS. In MNNSS, disturbance of incidents to the location determination results can be avoided by using more access points in each compare. In further research, we can focus on following aspects: Using more layers in our calculation can provide more location determination accuracy, but the costs of calculation will increase.

Let SP = {V | V ∈ Ω ∧ |V | = M }, where |V | denotes the cardinality of V . Find a polygon P ∈ SP such that E(P, C) = min E(V, C). 1 Overview of Split and Merge Techniques Split Technique Traditional split technique is a very simple method for solving polygonal approximation problem. It is a recursive method starting with an initial curve segmentation. At each iteration, a split procedure is conducted to split the segment at the selected point unless the obtained polygon satisfy the specified constraint condition.

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