Results 101 to 110 of about 7,156,184 (249)
Multi-sensory environment analysis and human activity recognition via wearable technologies
, 2015 S.2-11The sensing of human activities and user surrounding environments is an essential topic in computer science. Application domains include the Ambient Assisted Living (AAL), healthcare, sports gear and military use cases.
Haescher, Marian
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FEBS Letters, EarlyView.Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley +1 more source
Automated Annotation of Sensor data for Activity Recognition using Deep Learning
, 2017 Within this work-in-progress, we aim to automate the annotation of Sensor data for generating training data for Activity Recognition (AR) of multiple persons. Usually, the activities are executed and recorded from test persons under the supervision of an
Ringsleben, Frederic +3 more
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Optimizing Trajectories Clustering for Activity Recognition [PDF]
, 2008 International audienceThis work aims at recognizing activities from large video datasets, using the object trajectories as the activity descriptors. We make usage of a compact structure based on 6 features to represent trajectories. This structure allows
Bremond, François +4 more
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FEBS Letters, EarlyView.Ascidian Ciona larvae initially show strong clockwise tail twisting, which is largely corrected during development. However, a small residual twist remains. This study shows that organized helical myofibrils in tail muscles mechanically stabilize this residual asymmetry, preventing complete restoration of bilateral symmetry and revealing how embryos ...
Yuki S. Kogure +3 more
wiley +1 more source
A Method to Human Activity Recognition Using Acceleration Databy Machine Learning [PDF]
, 2020 In this paper, we proposed a method to identify human behavior using a 3-axis acceleration sensor of a smartphone. To realize context-aware services such as efficient energy-saving appliance controland elderly monitoring, high-accuracy in-home living ...
白井, 治彦 +9 more
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The human gut microbiome across the life course
FEBS Letters, EarlyView.Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero +4 more
wiley +1 more source
ShoeTect2.0: Real-Time Activity Recognition Using MobileNet CNN with Multisensory Smart Footwear
260268In this paper, we introduce a proof-of-concept multi-sensory footwear prototype with artificial intelligence to facilitate human activity recognition.
Matthies, Denys +3 more
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FEBS Letters, EarlyView.Septin 9 polybasic domains couple phosphoinositide‐rich membrane binding to centrosome positioning, Golgi organization, and microtubule acetylation to control epithelial polarity. Their loss disrupts this axis, causing centrosome mispositioning, Golgi fragmentation, reduced microtubule acetylation, and polarity inversion via upregulation of the ...
Ting ting Cai +4 more
wiley +1 more source
Location-Based Activity Recognition [PDF]
, 2007 Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a person's activities and significant places from traces of GPS data. In contrast to existing techniques, our approach simultaneously detects and classifies the significant locations of a person and takes the ...
openaire +1 more source