High-Precision Indoor Visible Light Positioning Using Modified Momentum Back Propagation Neural Network with Sparse Training Point.

In this letter, we propose an indoor visible light positioning technique using a Modified Momentum Back-Propagation (MMBP) algorithm based on received signal strength (RSS) with sparse training data set. Unlike other neural network algorithms that require a large number of training data points to locate accurately, we have realized high-precision positioning for 100 test points with only 20 training points in a 1.8 m × 1.

Hybrid indoor localization scheme with image sensor-based visible light positioning and pedestrian dead reckoning.

In this paper, we propose a hybrid indoor localization scheme with image sensor-based visible light positioning and pedestrian dead reckoning. The architecture and algorithm of the proposed positioning scheme are analyzed. We build and demonstrate two different positioning prototypes with single/multiple cells, which are based on a commercial light-emitting diode lamp and off-the-shelf mobile phone equipped with an image sensor and inertial measurement unit.

Novel two-tiered approach of ecological risk assessment for pesticide mixtures based on joint effects.

Ecological risk assessments for mixtures have attracted considerable attention. In this study, 38 pesticides in the real environment were taken as objects and their toxicities to different organisms from three trophic levels were employed to assess the ecological risk of the mixture. The first tier assessment was based on the CA effect and the obtained sum of risk quotients (SRQ) were 3.