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 various intelligent applications, such as those for remote health and lifestyle monitoring, intelligent personalized services, etc.However, activity context recognition base

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Bacteria in Cancer Therapy: Renaissance of an Old Concept

The rising incidence of cancer cases worldwide generates an urgent need of novel treatment options.Applying bacteria may represent a valuable therapeutic variant that is intensively investigated nowadays.Interestingly, the idea to apply bacteria wittingly or unwittingly dates back to ancient times and was revived in the 19th century mainly by the p

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Esophageal disorders in patients with irritable bowel syndrome

Aim.To study the whole range of esophageal disorders in patients with irritable bowel syndrome (IBS) using high-tech 711719541028 methods.Materials and methods.102 IBS patients (47 males, mean age 40.8, diagnosis of IBS was established according to Rome III criteria) with esophageal symptoms (heartburn, belching, globus sensation and noncardiac che

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Long-Term Probabilistic Volcanic Hazard Assessment Using Open and Non-open Data: Observations and Current Issues

Probabilistic volcanic hazard assessment (PVHA) has become the paradigm to quantify volcanic hazard over the last decades.Substantial aleatory and epistemic uncertainties in PVHA arise from complexity of physico-chemical processes, impossibility of their direct observation and, importantly, a severe scarcity of observables from past eruptions.One f

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