DEEP SENSING: INERTIAL AND AMBIENT SENSING FOR ACTIVITY CONTEXT RECOGNITION USING DEEP CONVOLUTIONAL NEURAL NETWORKS

Deep Sensing: Inertial and Ambient Sensing for Activity Context Recognition Using Deep Convolutional Neural Networks

With the widespread use of embedded sensing capabilities of mobile devices, there has been unprecedented development of context-aware solutions.This allows the proliferation of Dipping Tools various intelligent applications, such as those for remote health and lifestyle monitoring, intelligent personalized services, etc.However, activity context re

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Enhanced Absence Sampling Technique for Data-Driven Landslide Susceptibility Mapping: A Case Study in Songyang County, China

Accurate prediction of landslide susceptibility relies on effectively handling absence samples in data-driven models.This study investigates the influence of different absence sampling methods, including buffer control sampling (BCS), controlled target space exteriorization sampling (CTSES), information value (IV), and mini-batch k-medoids (MBKM),

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Neutrophils in COVID-19

Strong evidence has been accumulated since the beginning of the COVID-19 pandemic that neutrophils play an important role in the pathophysiology, particularly in those with severe disease courses.While originally considered to be a rather homogeneous cell type, recent attention to neutrophils has uncovered their fascinating transcriptional Gifts an

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