Hierarchical Topology-Based Cluster Representation for Scalable Evolutionary Multiobjective Clustering

2021 ◽  
pp. 1-15
Author(s):  
Shuwei Zhu ◽  
Lihong Xu ◽  
Erik D. Goodman
Keyword(s):  
Hierarchical Topology ◽  
Cluster Representation

Distance Density Based Clustering Algorithm in Wireless Sensor Network

2011 ◽  
Vol 291-294 ◽  
pp. 344-348
Author(s):  
Lin Lin ◽  
Shu Yan ◽  
Yi Nian
Keyword(s):  
Clustering Algorithm ◽  
Distribution Density ◽  
Simulation Experiment ◽  
Clustering Algorithms ◽  
Wireless Sensor ◽  
Energy Usage ◽  
Cluster Heads ◽  
Hierarchical Topology ◽  
Energy Factors ◽  
Density Based Clustering

The hierarchical topology of wireless sensor networks can effectively reduce the consumption in communication. Clustering algorithm is the foundation to realize herarchical structure, so it has been extensive researched. On the basis of Leach algorithm, a distance density based clustering algorithm (DDBC) is proposed, considering synthetically the distribution density of around nodes and the remaining energy factors of the node to dynamically banlance energy usage of nodes when selecting cluster heads. We analyzed the performance of DDBC through compared with the existing other clustering algorithms in simulation experiment. Results show that the proposed method can generare stable quantity cluster heads and banlance the energy load effectively.

scholarly journals Key Bacteria in the Gut Microbiota Network for the Transition between Sedentary and Active Lifestyle

2020 ◽  
Vol 8 (5) ◽  
pp. 785
Author(s):  
Nazareth Castellanos ◽  
Gustavo G. Diez ◽  
Carmen Antúnez-Almagro ◽  
Carlo Bressa ◽  
María Bailén ◽  
...  
Keyword(s):  
Physical Activity ◽  
Gut Microbiota ◽  
Health Benefits ◽  
Active Lifestyle ◽  
Hierarchical Topology ◽  
Microbial Network ◽  
Novel Method ◽  
Overall Efficiency

Physical activity modifies the gut microbiota, exerting health benefits on the host; however, the specific bacteria associated with exercise are not yet known. In this work, we propose a novel method, based on hierarchical topology, to study the differences between the microbiota of active and sedentary lifestyles, and to identify relevant bacterial taxa. Our results show that the microbiota network found in active people has a significantly higher overall efficiency and higher transmissibility rate. We also identified key bacteria in active and sedentary networks that could be involved in the conversion of an active microbial network to a sedentary microbial network and vice versa.

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