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However, using MIMO-OFDM CSI as the observation data for localization based on AOA is of particular interest here, due to the following reasons.
Recently, it has been shown that multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) channel state information (CSI) may be used as the observation data for localization based on AOA [9].
Patients allocated to the experimental group were operated on under general anesthesia in the knee-elbow position; no bony decompression was done, and an interspinous process device was implanted by a posterior midline approach using radiographic data for localization of the appropriate level.
To determine the subcellular localization of HA-tagged PfCK2α [ 19], PfCK2β1 or PfCK2β2 subunits, we examined these transgenic lines in IFAs using antibodies against the HA epitope and against Exp2, a parasitophorous vacuole marker [ 32] (data for localization of all three subunits are presented in Figure 2A-C).
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On top of this localization, various conditions are introduced to reflect requirements occurring during fabrication such as minimum cutting length, maintenance of cutting length, localization for non-penetration and data types for localization.
According to the proposed method, the CSI obtained by the MIMO-OFDM receivers of all APs upon successful reception of a data packet from a mobile terminal (MT) is processed in order to determine the location of the MT. We assume that the MT uses only one antenna, i.e., one spatial stream, for transmitting the data packet for localization.
Other contributions include the framework to use the BIM data for indoor localization, and the algorithm incorporating the data.
To provide good input data for our localization algorithms, we set up the test environment as shown in Figure 10.
In this paper, all phases for through wall tracking are outlined whereas the attention is devoted to the estimation of the correct input data for the localization phase.
All phases for through wall tracking are outlined whereas the attention is devoted to the estimation of the correct input data for the localization phase.
We give examples of using the tool to present Arabidopsis gene expression data from the AtGenExpress Consortium (Arabidopsis eFP Browser), data for subcellular localization of Arabidopsis proteins (Cell eFP Browser), and mouse tissue atlas microarray data (Mouse eFP Browser).
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