An indoor positioning approach using sibling signal patterns in enterprise WiFi infrastructure

The indoor positioning technology plays an important role in the application scenarios requiring indoor location. In this paper, the WiFi signals under modern enterprise WiFi infrastructure and signal patterns between coexisting access points (APs) are investigated. Sibling signal patterns are defined and processed to generate Beacon APs that have higher confidence for positioning. Then a positioning approach using Beacon APs is proposed and shows improved positioning accuracy. The proposed schemes are fully designed, implemented and evaluated in a real-world environment, revealing its effectiveness and efficiency

Structure-Induced Reversible Anionic Redox Activity in Na Layered Oxide Cathode

Anionic redox reaction (ARR) in lithium- and sodium-ion batteries is under hot discussion, mainly regarding how oxygen anion participates and to what extent oxygen can be reversibly oxidized and reduced. Here, a P3-type Na0.6[Li0.2Mn0.8]O2 with reversible capacity from pure ARR was studied. The interlayer O-O distance (peroxo-like O-O dimer, 2.506(3) Å), associated with oxidization of oxygen anions, was directly detected by using a neutron total scattering technique. Different from Li2RuO3 or Li2IrO3 with strong metal-oxygen (M-O) bonding, for P3-type Na0.6[Li0.2Mn0.8]O2 with relatively weak Mn-O covalent bonding, crystal structure factors might play an even more important role in stabilizing the oxidized species, as both Li and Mn ions are immobile in the structure and thus may inhibit the irreversible transformation of the oxidized species to O2 gas. Utilization of anionic redox reaction (ARR) on oxygen has been considered as an effective way to promote the charge-discharge capacity of the layered oxide cathodes for lithium- or sodium-ion batteries. The detailed mechanism of ARR, in particular how crystal structure affects and coordinates with the ARR, is not yet well understood. In the present work, a combination of X-ray and neutron total scattering measurements has been performed to study the structure of the prototype P3-type layered Na0.6[Li0.2Mn0.8]O2 with pure ARR. Unique structural characteristics, rather than prevailing knowledge of covalency of metal-oxygen, enable the stabilization of the crystal structure of Na0.6[Li0.2Mn0.8]O2 along with the ARR. This work suggests that reversible ARR can be manipulated by proper structure designs, thus to achieve high lithium or sodium storage in layered oxide cathodes. For P3-type Na0.6[Li0.2Mn0.8]O2 with relatively weak Mn-O covalent bonding, crystal structure factors play an important role in stabilizing the oxidized species, inhibiting the irreversible transformation of the oxidized species to O2 gas. The finding is important for better design of layered oxide positive materials with higher reversible capacity via the introduction of a reversible anionic redox reaction

Bias adjustment of satellite-based precipitation estimation using gauge observations: A case study in Chile

Satellite-based precipitation estimates (SPEs) are promising alternative precipitation data for climatic and hydrological applications, especially for regions where ground-based observations are limited. However, existing satellite-based rainfall estimations are subject to systematic biases. This study aims to adjust the biases in the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Cloud Classification System (PERSIANN-CCS) rainfall data over Chile, using gauge observations as reference. A novel bias adjustment framework, termed QM-GW, is proposed based on the nonparametric quantile mapping approach and a Gaussian weighting interpolation scheme. The PERSIANN-CCS precipitation estimates (daily, 0.04°×0.04°) over Chile are adjusted for the period of 2009–2014. The historical data (satellite and gauge) for 2009–2013 are used to calibrate the methodology; nonparametric cumulative distribution functions of satellite and gauge observations are estimated at every 1°×1° box region. One year (2014) of gauge data was used for validation. The results show that the biases of the PERSIANN-CCS precipitation data are effectively reduced. The spatial patterns of adjusted satellite rainfall show high consistency to the gauge observations, with reduced root-mean-square errors and mean biases. The systematic biases of the PERSIANN-CCS precipitation time series, at both monthly and daily scales, are removed. The extended validation also verifies that the proposed approach can be applied to adjust SPEs into the future, without further need for ground-based measurements. This study serves as a valuable reference for the bias adjustment of existing SPEs using gauge observations worldwide