Results 241 to 250 of about 9,468,510 (297)

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

Advanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar, Zhengtong Xu, Siavash Mahmoudi, Pouya Sohrabipour, Chaitanya Pallerla, Yu She, Wan Shou, Philip Glen Crandall, Dongyi Wang   +8 more
wiley   +1 more source

A Retrospective Analysis Examining the Impact of Educational Attainment and Social Determinants of Health on Rifampicin-Resistant Tuberculosis Treatment Outcomes. [PDF]

Open Forum Infect Dis
Teibo TKA, Perumal R, Amusa LB, Shunmugam L, Mzinyane N, Chetty D, Boodhram R, Narasimmulu R, Kachoka T, Shozi C, O'Donnell MR, Wolf A, Chotoo S, Singh N, Arcêncio RA, Padayatchi N, Naidoo K.   +16 more
europepmc   +1 more source

Adverse Childhood Experiences and Life Course Depressive Symptoms: Do Peer Network Ties Buffer or Amplify? [PDF]

Soc Ment Health
Kamis C, Copeland M.
europepmc   +1 more source

Unveiling local dependencies in accuracy and speed: A mixture hierarchical modeling approach. [PDF]

Behav Res Methods
Huang HY.
europepmc   +1 more source

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Latent Class Model Diagnosis

Biometrics, 2000
Summary.In many areas of medical research, such as psychiatry and gerontology, latent class variables are used to classify individuals into disease categories, often with the intention of hierarchical modeling. Problems arise when it is not clear how many disease classes are appropriate, creating a need for model selection and diagnostic techniques ...
Garrett, Elizabeth S., Zeger, Scott L.
openaire   +2 more sources

Latent class CUB models

Advances in Data Analysis and Classification, 2013
The paper proposes a latent class version of Combination of Uniform and (shifted) Binomial random variables ( CUB ) models for ordinal data to account for unobserved heterogeneity. The extension, called LC-CUB , is useful when the heterogeneity is originated by clusters of respondents not identified by covariates: this may generate a multimodal ...
Leonardo Grilli, Maria Iannario, Domenico Piccolo, Carla Rampichini   +3 more
openaire   +3 more sources