Towards a Model Based on Agents for the Detection of Behavior Patterns in Older Adults Who Start Using ICT

2018 ◽  
pp. 261-268
Author(s):  
Consuelo Salgado Soto ◽  
Maricela Sevilla Caro ◽  
Ricardo Rosales Cisneros ◽  
Margarita Ramírez Ramírez ◽  
Hilda Beatriz Ramírez Moreno ◽  
...  
Keyword(s):  
Older Adults ◽  
Behavior Patterns ◽  
Model Based

scholarly journals A model-based approach to attention and sensory integration in postural control of older adults

2007 ◽  
Vol 429 (2-3) ◽  
pp. 147-151 ◽  
Author(s):  
Arash Mahboobin ◽  
Patrick J. Loughlin ◽  
Mark S. Redfern
Keyword(s):  
Older Adults ◽  
Postural Control ◽  
Sensory Integration ◽  
Model Based

scholarly journals Mobility Prediction Using a Weighted Markov Model Based on Mobile User Classification

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1740
Author(s):  
Ming Yan ◽  
Shuijing Li ◽  
Chien Aun Chan ◽  
Yinghua Shen ◽  
Ying Yu
Keyword(s):  
Prediction Model ◽  
Mobile Communication ◽  
Historical Data ◽  
Mobile User ◽  
Machine Learning Algorithms ◽  
Behavior Patterns ◽  
Mobility Prediction ◽  
User Classification ◽  
Model Based ◽  
Weighting Coefficients

The vast amounts of mobile communication data collected by mobile operators can provide important insights regarding epidemic transmission or traffic patterns. By analyzing historical data and extracting user location information, various methods can be used to predict the mobility of mobile users. However, existing prediction algorithms are mainly based on the historical data of all users at an aggregated level and ignore the heterogeneity of individual behavior patterns. To improve prediction accuracy, this paper proposes a weighted Markov prediction model based on mobile user classification. The trajectory information of a user is extracted first by analyzing real mobile communication data, where the complexity of a user’s trajectory is measured using the mobile trajectory entropy. Second, classification criteria are proposed based on different user behavior patterns, and all users are classified with machine learning algorithms. Finally, according to the characteristics of each user classification, the step threshold and the weighting coefficients of the weighted Markov prediction model are optimized, and mobility prediction is performed for each user classification. Our results show that the optimized weighting coefficients can improve the performance of the weighted Markov prediction model.

scholarly journals Integrative omics approach to identify the molecular architecture of inflammatory protein levels in healthy older adults

2020 ◽  
Author(s):  
Robert F. Hillary ◽  
Daniel Trejo-Banos ◽  
Athanasios Kousathanas ◽  
Daniel L. McCartney ◽  
Sarah E. Harris ◽  
...  
Keyword(s):  
Older Adults ◽  
Mixed Model ◽  
Association Studies ◽  
Ordinary Least Squares ◽  
Causal Relationships ◽  
Molecular Architecture ◽  
Healthy Older Adults ◽  
Protein Levels ◽  
Model Based ◽  
Inflammatory Protein

AbstractThe molecular factors which control circulating levels of inflammatory proteins are not well understood. Furthermore, association studies between molecular probes and human traits are often performed by linear model-based methods which may fail to account for complex structure and interrelationships within molecular datasets. Therefore, in this study, we perform genome- and epigenome-wide association studies (GWAS/EWAS) on the levels of 70 plasma-derived inflammatory protein biomarkers in healthy older adults (Lothian Birth Cohort 1936; n = 876; Olink® inflammation panel). We employ a Bayesian framework (BayesR+) which can account for issues pertaining to data structure and unknown confounding variables (with sensitivity analyses using ordinary least squares- (OLS) and mixed model-based approaches). We identified 13 SNPs associated with 13 proteins (n = 1 SNP each) concordant across OLS and Bayesian methods. We identified three CpG sites spread across three proteins (n = 1 CpG each) that were concordant across OLS, mixed-model and Bayesian analyses. Tagged genetic variants accounted for up to 45% of variance in protein levels (for MCP2, 36% of variance alone attributable to one polymorphism). Methylation data accounted for up to 46% of variation in protein levels (for CXCL10). Up to 66% of variation in protein levels (for VEGFA) was explained using genetic and epigenetic data combined. We demonstrated putative causal relationships between CD6 and IL18R1 with inflammatory bowel disease, and between IL12B and Crohn’s disease. Our data may aid understanding of the molecular regulation of the circulating inflammatory proteome as well as causal relationships between inflammatory mediators and disease.

Personality and Emotional Intelligence in Older Adults: A Predictive Model Based on Structural Equations Modeling

2018 ◽  
Vol 153 (2) ◽  
pp. 237-246
Author(s):  
Iraida Delhom ◽  
Margarita Gutierrez ◽  
Beatriz Lucas-Molina ◽  
Encarna Satorres ◽  
Juan C. Meléndez
Keyword(s):  
Older Adults ◽  
Emotional Intelligence ◽  
Predictive Model ◽  
Structural Equations ◽  
Structural Equations Modeling ◽  
Model Based
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