main webpage W Topic Hand In My Pocket arXiv (Cornell University) Gait-Based Hand Load Estimation via Deep Latent Variable Models with Auxiliary Information 2025 Machine learning methods are increasingly applied to ergonomic risk assessment in manual material handling, particularly for estimating carried load from gait motion data collected from wearable sensors. However, existing approaches often rely on direct mappi… Article Open Hand In My Pocket Open Article Page

Hand In My Pocket

1995 single by Alanis Morissette " Hand in My Pocket " is a song by Canadian recording artist and songwriter Alanis Morissette from her third studio album, Jagged Little Pill (1995). The song was written by Morissette and Glen Ballard and was released as the album's second single (third in Japan) on October 16, 1995, by Maverick and Reprise Records. The song received generally favorable reviews from music critics, who applauded Morissette's songwriting. "Hand in My Pocket" also received substantial success through radio airplay in the US. The song became Morissette's second number-one hit on the US Billboard Modern Rock Tracks chart. The song also reached the top 10 in New Zealand and Canada, where it was her first number-one single. Critical Symbolic Virtual Narrative Open Hand In My Pocket Open Article Page

Exploring foci of: arXiv (Cornell University) Gait-Based Hand Load Estimation via Deep Latent Variable Models with Auxiliary Information 2025 Machine learning methods are increasingly applied to ergonomic risk assessment in manual material handling, particularly for estimating carried load from gait motion data collected from wearable sensors. However, existing approaches often rely on direct mappings from loaded gait to hand load, limiting generalization and predictive accuracy. In this study, we propose an enhanced load estimation framework that incorporates auxiliary information, including baseline gait patterns during unloaded walking and carrying s… Open Article Page

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Explore Hand In My Pocket W Topic Hand In My Pocket arXiv (Cornell University) Gait-Based Hand Load Estimation via Deep Latent Variable Models with Auxiliary Information 2025 Machine learning methods are increasingly applied to ergonomic risk assessment in manual material handling, particularly for estimating carried load from gait motion data collected from wearable sensors. However, existing approaches often rely on direct mappi… Article Critical Symbolic Virtual Narrative Open Hand In My Pocket Open Article Page