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A Network of Dynamic Probabilistic Models for Human Interaction Analysis

Heung-Il Suk, A. K. Jain, Seong-Whan Lee
2011 IEEE transactions on circuits and systems for video technology (Print)  
a robust model for the analysis of human interactions.  ...  Index Terms-Dynamic Bayesian network, human interaction analysis, network of dynamic probabilistic models, subinteractions, video surveillance.  ...  Chen for providing Tsinghua University's dataset for performance comparison.  ... 
doi:10.1109/tcsvt.2011.2133570 fatcat:bqnkcmfsmfeg3jh3z32fhs433e

Simulation-based Probabilistic Risk Assessment [article]

Tarannom Parhizkar
2022 arXiv   pre-print
In this regard, multiple statistical and probabilistic tools can be used to provide a valuable assessment of dynamic probabilistic risk levels in different applications.  ...  Based on the reviewed literature, SPRA methods can be classified into three categories of dynamic probabilistic logic methods, dynamic stochastic analytical models, and hybrid discrete dynamic event and  ...  In this methodology, a dynamic Bayesian network is adapted for risk management of complex engineering systems.  ... 
arXiv:2207.12575v1 fatcat:br3xhpihazaz7hcm2w7ozriivm

Network Biology in Medicine and Beyond

B. Zhang, Y. Tian, Z. Zhang
2014 Circulation: Cardiovascular Genetics  
Biological networks provide a conceptual and intuitive framework to investigate, model, characterize, and understand complex interactions of different components in a biological system.  ...  The complexity of a biological system is reflected in part by a large number of interacting variables, the dynamics of which are governed by numerous linear or nonlinear relationships, chemical kinetics  ...  Sources of Funding Disclosures None.  ... 
doi:10.1161/circgenetics.113.000123 pmid:25140061 pmcid:PMC4333150 fatcat:bobjv3d5xzcttgtvng5vcf7x2a

Event Based Dynamic Context Model for Group Interaction Analysis(Contribution to 21 Century Intelligent Technologies and Bioinformatics)

Peng DAI, Linmi TAO, Guangyou XU
2008 International journal of biomedical soft computing and human sciences  
T7iis paperpresents a novel Event Based Qynamie Cbntext Model to represent hierarchical interaction context and soive the problems of context mvareness.  ...  VZ)vember 200rp China Abstract: Cbmputer understancfing ofhuman sociai interactions is a challenging tqpic in the.field ofhuman eomputiug due to its muitizparty dynamic natune andmultimodnl characteristics  ...  In our experiments, a fiexible coarse-to-fine processing strategy and a refined probabilistic model are introduced respectively for online analysis.  ... 
doi:10.24466/ijbschs.13.2_67 fatcat:3gqcjrvolfabxjpf5g7box5cvq

Challenges on Probabilistic Modeling for Evolving Networks [article]

Jianguo Ding, Pascal Bouvry
2013 arXiv   pre-print
This paper presents a survey on probabilistic modeling for evolving networks and identifies the new challenges which emerge on the probabilistic models and optimization strategies in the potential application  ...  Due to the complexity of emerging networks, it is not always possible to build precise models in modeling and optimization (local and global) for networks.  ...  Probabilistic Modeling for Dynamic Networks The goal of modelling for evolving networks is to model the state of a system and its evolution over time in a richer and more natural way.  ... 
arXiv:1304.7820v2 fatcat:qvtskgtvpvh2npqbyjlghyu774

Human Synchronization Maps—The Hybrid Consciousness of the Embodied Mind

Franco Orsucci
2021 Entropy  
Thus, multidimensional theoretical models can represent the hybrid nature of human interactions.  ...  Cluster analysis and Markov chains produced evidence of chimaera states and phase transitions. A probabilistic and nondeterministic approach clarified the properties of these hybrid dynamics.  ...  Of further interest for human dynamics is the emergence of chimaera states in multiscale networks that result from the networking of different networks [50, 51] .  ... 
doi:10.3390/e23121569 pmid:34945875 pmcid:PMC8700702 fatcat:6l45yeisyrhnjlzawk3d3wjtwi

Sensitivity analysis of human lower extremity joint moments due to changes in joint kinematics

Marzieh M. Ardestani, Mehran Moazen, Zhongmin Jin
2015 Medical Engineering and Physics  
Despite the widespread applications of human gait analysis, causal interactions between joint kinematics and joint moments have not been well documented.  ...  Multi-body dynamics analysis was then used to calculate joint moments with respect to the probabilistic gait cycles.  ...  A forward dynamic model of gait with application to stress analysis of bone. 19 21. Lim C, Jones N, Spurgeon SK, Scott J.  ... 
doi:10.1016/j.medengphy.2014.11.012 pmid:25553962 fatcat:dctvb3o6x5b7tmycfzxadyqjcu

Representing dynamic biological networks with multi-scale probabilistic models

Alexander Groß, Barbara Kracher, Johann M. Kraus, Silke D. Kühlwein, Astrid S. Pfister, Sebastian Wiese, Katrin Luckert, Oliver Pötz, Thomas Joos, Dries Van Daele, Luc De Raedt, Michael Kühl (+1 others)
2019 Communications Biology  
As an example of a comprehensive model of signal transduction, we provide a Wnt network that shows remarkable robustness under a range of phenotypical and pathological conditions.  ...  Dynamic models analyzing gene regulation and metabolism face challenges when adapted to modeling signal transduction networks.  ...  Discussion ProbRules is a novel probabilistic modeling approach for integrating multi-scale knowledge about the dynamics of interactions.  ... 
doi:10.1038/s42003-018-0268-3 pmid:30675519 pmcid:PMC6336720 fatcat:u7dyb4bf55h7lidbzx6rpy3mwy

Different Methods of Accident Forecast Based on Real Data

Gajendran C Serin VK
2015 Journal of Civil & Environmental Engineering  
System dynamics is a computer-aided approach to policy analysis and design.  ...  This model was developed using STELLA a System Dynamic Model software .The main objective for the studies is to predict the expected number of accidents from 2010-2020.  ... 
doi:10.4172/2165-784x.1000180 fatcat:fv3ar76effcybbjhrhyx7y5564

Dynamic Bayesian Networks for Musical Interaction [chapter]

Baptiste Caramiaux, Jules Françoise, Frédéric Bevilacqua
2017 The Routledge Companion to Embodied Music Interaction  
Acknowledgements This work is supported by the Marie Sk lodowska-Curie Action of the European Union (H2020-MSCA-IF-2014, IF-GF, grant agreement no. 659232) and by the Rapid-Mix EU project (H2020-ICT-2014  ...  These models are probabilistic and can be unified and generalized under the formalism of dynamic Bayesian networks (DBNs).  ...  In addition, the probabilistic nature of DBNs allows for modeling of spatiotemporal variations inherent to human motion.  ... 
doi:10.4324/9781315621364-39 fatcat:dwxlqzzufvhr7mlwbmpng25iim

Leading or Following? Dyadic Robot Imitative Interaction Using the Active Inference Framework

Nadine Wirkuttis, Jun Tani
2021 IEEE Robotics and Automation Letters  
In a set of simulation studies, we examine dyadic imitative interactions of robots using a variational recurrent neural network model.  ...  We examined how regulating the complexity term to minimize free energy determines the dynamic characteristics of networks and interactions.  ...  Special thanks goes to Fabien Benuerau and Jeffrey Queisser, for fruitful discussions about developing the computational model.  ... 
doi:10.1109/lra.2021.3090015 fatcat:gd52mlxrkbfajc336hiudewcza

The network organization of protein interactions in the spliceosome is reproduced by the simple rules of food-web models

Mathias M. Pires, Maurício Cantor, Paulo R. Guimarães, Marcus A. M. de Aguiar, Sérgio F. dos Reis, Patricia P. Coltri
2015 Scientific Reports  
We then investigated the role of affinity and specificity in shaping the spliceosome network by adapting a probabilistic model originally designed to reproduce food webs.  ...  Conversely, a network has a nested strucuture when the set of elements interacting with poorly-connected elements also interact with highly-connected elements.  ...  The good fit of the PNM to a protein-protein network endorses the use of a similar approach, based on network models, to study the dynamics of complex subcellular systems.  ... 
doi:10.1038/srep14865 pmid:26443080 pmcid:PMC4595644 fatcat:hunvlzon4fgt3c5udthqkz4gdm

Computational dynamic approaches for temporal omics data with applications to systems medicine

Yulan Liang, Arpad Kelemen
2017 BioData Mining  
This is key for understanding the complexity of the human health, drug response, disease susceptibility and pathogenesis for systems medicine.  ...  In this paper, we present various recently developed dynamic trajectory and causal network approaches for temporal omics data, which are extremely useful for those researchers who want to start working  ...  Availability of data and materials Data sharing not applicable to this article as no datasets were generated or analysed during the current study.  ... 
doi:10.1186/s13040-017-0140-x pmid:28638442 pmcid:PMC5473988 fatcat:rscvtjlpgrf53fbwlt6t4i22em

Disentangling Interactions in the Microbiome: A Network Perspective

Mehdi Layeghifard, David M. Hwang, David S. Guttman
2017 Trends in Microbiology  
We discuss emerging graph theoretical concepts and approaches used in other research disciplines and demonstrate how they are well suited for enhancing our understanding of the higher-order interactions  ...  Network-based analytical approaches have the potential to help disentangle complex polymicrobial and microbe-host interactions, and thereby further the applicability of microbiome research to personalized  ...  An alternative to LSA is using Bayesian network models. There are two types of Bayesian network model for dynamic processes: dynamic Bayesian networks (DBNs), and temporal event networks (TENs).  ... 
doi:10.1016/j.tim.2016.11.008 pmid:27916383 pmcid:PMC7172547 fatcat:3zcr5exogfce5hizfqcr6grflm

Controlling the Sense of Agency in Dyadic Robot Interaction: An Active Inference Approach [article]

Nadine Wirkuttis, Jun Tani
2021 arXiv   pre-print
In a set of simulation studies, we examine dyadic imitative interactions of robots using a variational recurrent neural network model.  ...  We examined how regulating the complexity term to minimize free energy during training determines the dynamic characteristics of networks and affects dyadic imitative interactions.  ...  For brevity, training analysis is reported only for the network that was trained on the probabilistic sequence A20%B80%C. Training of A80%B20%C showed comparable results.  ... 
arXiv:2103.02137v1 fatcat:iyywsoqzfve7zeeiq22yedd3uq
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