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In Section "Experimental results", we present the results of indoor localization experiments based on the CSS ranging.
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Based on the 2015 CSS data, after converting household property assets per capita into present value, the Gini Coefficient represented by property assets reaches approximately 0.6.
In Palm's own words, webOS' Mojo framework is "a new application framework based on the HTML5, CSS, and JavaScript standards".
Based on the 2013 CSS data, it is shown that, as income increases, some social classes (the new middle class, old middle class, and working class) allocate a comparatively larger proportion of their disposable income to consumption than others do (i.e. business owners and peasants).
Based on the first TSEEOB-CSS algorithm, another algorithm is proposed.
Based on the decision fusion criteria, CSS can be realized in either a centralized or a distributed manner.
Moreover, based on the multivariate analysis of CSS, high STMN1 expression translated into an independent prognostic factor.
Thus, a second TSEEOB-CSS algorithm is proposed based on the first one, and its structure can also be described in Figure 2. The second TSEEOB-CSS scheme is represented by the following steps: Step 1: Perform the first stage coarse energy detection with α N s samples at each SU as in Equation (6).
Thus, the second TSEEOB-CSS algorithm is proposed based on the first one, which uses the local decision of the coarse detection to improve the energy efficiency of the algorithm with the same length of sensing time.
As described above, meta-SS and CSS are based on the P-values and the test statistics of the elementary tests, respectively.
CSS ranging is based on the time of flight (TOF) of radio frequency signals.
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