Results 81 to 90 of about 207,453 (329)

Modeling sequences and temporal networks with dynamic community structures

open access: yes, 2017
In evolving complex systems such as air traffic and social organizations, collective effects emerge from their many components' dynamic interactions. While the dynamic interactions can be represented by temporal networks with nodes and links that change ...
Peixoto, Tiago P., Rosvall, Martin
core   +2 more sources

Modeling dynamic reliability using dynamic Bayesian networks

open access: yesJournal Européen des Systèmes Automatisés, 2006
This paper considers the problem of modeling and analyzing the reliability of a system or a component (system) where the state of the system and the state of process variables influences each other in addition to an exogenous perturbation influence: this is the dynamic reliability. We consider discrete time case, that is the state of the system as well
Tchangani, Ayeley, Noyes, Daniel
openaire   +3 more sources

Hard‐Magnetic Soft Millirobots in Underactuated Systems

open access: yesAdvanced Robotics Research, EarlyView.
This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang   +4 more
wiley   +1 more source

River‐Floodplain Metacommunities as Complex Networks: The Interplay of Species Interactions, Dispersal, and Environment

open access: yesEnvironmental DNA
Dynamic heterogeneous metacommunities can be analyzed as complex networks. However, the interplay of species interactions, local environmental conditions, and spatiotemporal dispersal remains poorly understood.
Andrea Funk   +8 more
doaj   +1 more source

Expectation propagation for large scale Bayesian inference of non-linear molecular networks from perturbation data. [PDF]

open access: yesPLoS ONE, 2017
Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell.
Zahra Narimani   +4 more
doaj   +1 more source

Multistream Dynamic Bayesian Network for Meeting Segmentation [PDF]

open access: yes, 2005
This paper investigates the automatic analysis and segmentation of meetings. A meeting is analysed in terms of individual behaviours and group interactions, in order to decompose each meeting in a sequence of relevant phases, named meeting actions. Three feature families are extracted from multimodal recordings: prosody from individual lapel microphone
Dielmann, Alfred, Renals, Steve
openaire   +3 more sources

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

open access: yesAdvanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu   +5 more
wiley   +1 more source

HyPE: Online Hybrid Pseudo-Bayesian Estimation Method for S-ALOHA-Based Tactical FANETs

open access: yesIEEE Access
Significant challenges are involved in tactical flying ad-hoc network (FANET) missions because network environments are very dynamic. In addition, energy-efficient network operation is important in tactical FANETs owing to the limited capacity of the on ...
Jimin Jeon   +7 more
doaj   +1 more source

Distributed Bayesian Filtering using Logarithmic Opinion Pool for Dynamic Sensor Networks [PDF]

open access: yes, 2018
The discrete-time Distributed Bayesian Filtering (DBF) algorithm is presented for the problem of tracking a target dynamic model using a time-varying network of heterogeneous sensing agents.
Bandyopadhyay, Saptarshi, Chung, Soon-Jo
core   +1 more source

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

open access: yesAdvanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek   +3 more
wiley   +1 more source

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