A NOVEL ALGORITHM TO DETECT NON-WEAR TIME FROM RAW ACCELEROMETER DATA USING DEEP CONVOLUTIONAL NEURAL NETWORKS

A novel algorithm to detect non-wear time from raw accelerometer data using deep convolutional neural networks

Abstract To date, non-wear detection algorithms commonly employ a 30, 60, or even 90 mins interval or window in which acceleration values need to be below a threshold value.A major drawback of such intervals is that they need to be long enough to prevent false positives (type I errors), while short enough to prevent false negatives Default (type II

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Relation between Changes in Photosynthetic Rate and Changes in Canopy Level Chlorophyll Fluorescence Generated by Light Excitation of Different Led Colours in Various Background Light

Using light emitting diodes (LEDs) for greenhouse illumination enables the use of automatic control, since both light quality and quantity can be tuned.Potential candidate signals when using biological feedback for light optimisation are steady-state chlorophyll a fluorescence gains at 740 nm, defined as the difference in steady-state fluorescence

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Research Methods in a Multinational Business Environment and Implications for Capital Formation: Application of Cross-Sectional Autoregressive Distributed Lag Methods

We explore whether foreign direct investment outflows augment or obstruct public or private capital in developing countries by decomposing domestic capital into private and public capital.While developed countries are the Glass Plates primary source of foreign direct investment outflows (FDIOs), developing economies have become the primary source o

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